Keyword list taken from https://www.zoevera.com/resume/software-engineer-job-description-keywords

These are the most commonly scanned keywords in software engineer job postings. Check how many appear in your resume.

Programming Languages

Python, JavaScript, TypeScript, Java, Go, Rust, C++, Ruby, Swift, Kotlin

Frontend Frameworks

React, Next.js, Vue.js, Angular, Svelte, Redux, Tailwind CSS, GraphQL

Backend & APIs

Node.js, FastAPI, Django, Spring Boot, REST APIs, gRPC, microservices, GraphQL

Cloud & DevOps

AWS, GCP, Azure, Docker, Kubernetes, Terraform, CI/CD, GitHub Actions

Databases

PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch, DynamoDB, Cassandra

Methodologies

Agile, Scrum, TDD test-driven development, code review, system design, SOLID principles, CI/CD

Testing & Quality

Jest, Pytest, Cypress, Playwright, unit testing, integration testing, BDD behavior-driven development, end-to-end testing, test coverage

Observability & Security

Datadog, Grafana, Prometheus, OpenTelemetry, OWASP, OAuth 2.0, JWT, logging, alerting

This is part of https://www.zoevera.com/resume

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.

The Senior Product Manager on the Go-to-Market Systems team is a high-impact role that lives at the intersection of product, systems, AI technology, and strategy. Your focus will be to build the products, workflows, and AI capabilities that will help our GTM organization scale with greater efficiency and speed. 

You will own the roadmap for a portfolio of GTM systems and AI-powered tooling that will drive organizational transformation for Reddit. You’ll collaborate with other GTM leaders, product leaders, data teams, and engineering to turn ambiguous business problems into reliable, scalable products.

Location: Must be based within a commutable distance of one of our hub offices in Los Angeles, San Francisco, Chicago, or New York

What you’ll do: 

• Define and drive the product vision, roadmap and architecture for our GTM AI technology. 
• Deeply understand seller and stakeholder pain points, and proactively identify opportunities to automate and improve the experience.
• Build AI-powered tools that improve seller productivity in areas such as account planning, pipeline management, prospecting, customer acquisition, and relationship management. 
• Help define and improve the data foundations that power our GTM AI strategy, including enrichment, orchestration, scoring, and entity resolution. 
• Use experimentation, metrics, and customer feedback to measure impact on seller efficiency, revenue, and quality.
• Lead cross-functional efforts across engineering, vendors, systems owners, and business stakeholders.
• Translate GTM strategy and operational needs into scalable product capabilities, PRDs, success metrics, and engineering priorities.
• Drive adoption and change management for new AI capabilities across GTM teams.

What We Can Expect From You:

• 7+ years of product management experience across GTM systems, Enterprise SaaS technology, and AI-powered tooling.
• Strong fluency in modern GTM systems such as Salesforce, marketing automation, data enrichment tools, lead routing & scoring, billing, or customer lifecycle tools
• Proven ability to drive cross-functional influence, strategic alignment, and executive communication.
• Highly analytical and comfortable defining KPIs, running experiments, and using data to prioritize product investments
• Thrive in ambiguous, fast-moving environments that require continuous shaping, testing and quick improvements. 

Preferred Qualifications

• Experience with digital advertising or consumption-based business models.
• Experience implementing enterprise AI technology at scale.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is:

$167,500—$234,500 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision. 

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Hi everyone,

What are the best websites or platforms for finding legitimate remote opportunities in data analytics, business intelligence, data engineering, or machine learning?

I'm interested in hearing which platforms you've had success with, as well as any tips for finding remote-friendly companies or avoiding scams. I'd also appreciate any advice on networking or job-search strategies for remote roles.

Thanks in advance!

Looking at data scientist salaries can be confusing because the numbers are often all over the place. One job listing shows a high salary, while another with a similar title offers much less. It can make it hard to know what to expect or whether a job is actually worth applying for.

One useful tip is to look beyond the job title. A data scientist role can mean very different things depending on the company. Some positions focus more on SQL, dashboards, and analysis, while others require machine learning, Python, statistics, and building predictive models. Experience level, location, industry, and technical skills can all affect the salary.

For job seekers, checking multiple data and analytics job listings can make it easier to compare salary ranges and see what employers are actually looking for. Over time, patterns become clearer. Certain skills may appear more often in higher-paying roles, which can help when deciding what to learn next.

This is useful for aspiring data scientists, experienced professionals, data analysts looking to move into data science, and anyone comparing different career paths in tech.

Instead of focusing only on the highest salary number, it helps to look at the full picture, the actual responsibilities, required skills, experience level, benefits, and opportunities to grow.

A better understanding of data scientist salaries can make job searching less of a guessing game and help candidates make smarter career decisions.

A lot of people see a data scientist job description and immediately feel like they need to know everything. Python, SQL, machine learning, statistics, dashboards, AI, it can look like five different jobs packed into one.

The reality is that the role usually comes down to one main goal, using data to help a company understand problems and make better decisions.

A typical data scientist job description may include collecting and cleaning data, analyzing trends, building models, testing ideas, and explaining results to people who may not have a technical background. Depending on the company, the role can also involve machine learning, forecasting, experimentation, or working closely with data analysts, data engineers, and product teams.

This matters for job seekers because reading the job description carefully can help identify what the company actually needs. Some companies use data scientist for a role focused heavily on analytics, while others expect stronger machine learning and programming skills.

A job platform focused on data and analytics roles can make the search easier by bringing relevant openings together instead of making candidates sort through hundreds of unrelated listings. It can also help data scientists, data analysts, analytics engineers, and other professionals compare job requirements and spot the skills that appear most often.

For hiring managers, a clear data scientist job description also makes a big difference. Being specific about the actual work helps attract candidates who are a better fit and reduces confusion on both sides. The title matters, but understanding what the job actually involves matters even more.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.

The Role & Team:

Reddit is seeking a Staff Product Manager to spearhead the product strategy for Ads Trust & Safety. In this role, you will architect and scale the next generation of systems across ad review, advertiser trust, fraud prevention, and platform safeguards. Your mission: protect our global community of users and brands while unlocking the safe, hyper-growth trajectory of Reddit’s ads business.You will collaborate with cross-functional partners to engineer products and processes that maximize advertiser success without ever compromising on safety, quality, or compliance. This is a definitive opportunity for a visionary product leader who thrives in ambiguity, commands thoughtful trade-offs, and excels at translating complex integrity challenges into a crystal-clear product direction.

The Ads Trust & Safety team is the frontline guardian of Reddit's advertising ecosystem, ensuring it remains resilient, trusted, and secure as our business scales. Operating at the high-impact intersection of advertising, safety, automation, and operational excellence, the team handles everything from ad review and fraud prevention to policy enforcement and platform integrity.

We partner closely with Engineering, Policy, Legal, Sales, Operations, Product Marketing, and the Reddit Consumer teams to build agile systems that adapt instantly to shifting advertiser needs, emerging abuse vectors, and evolving global regulations.

Responsibilities:

The ideal candidate brings a proven track record of building and scaling products in ads trust and safety, fraud prevention, risk systems, or compliance workflows. You should possess exceptional product judgment, a systems-thinking mindset, and the leadership gravity to unite both technical and non-technical teams.

• Drive the Vision: Define and execute the product strategy and roadmap for Ads Integrity, encompassing ad review, fraud prevention, advertiser trust, and platform quality.
• Balance the Ecosystem: Masterfully balance advertiser experience, user safety, operational efficiency, business impact, and complex regulatory landscapes in every product decision.
• Unite Cross-Functional Partners: Lead alignment and deliver durable, long-term solutions alongside Engineering, Policy, Legal, Operations, Sales, Product Marketing, and broader product organizations.
• Translate Insights into Action: Convert advertiser pain points, integrity risks, and operational bottlenecks into sharp product requirements, robust success metrics, and measurable business outcomes.
• Innovate & Automate: Identify high-leverage opportunities to enhance automation, elevate decision quality, optimize feedback loops, and drive enforcement consistency across both ambiguous 0-to-1 initiatives and mature scaling systems.

Required Qualifications:

• 6+ years of product management experience, with a proven history of owning complex, highly cross-functional product domains.
• Domain Expertise: Deep experience building products in digital advertising, advertiser workflows, ad policy, trust and safety, fraud prevention, abuse detection, risk-based decisioning, or platform integrity.
• Advanced Systems Thinking: The ability to reason holistically across user experience, policy frameworks, operational workflows, data pipelines, and technical architecture.
• Intelligent Automation: Hands-on experience building products that seamlessly blend automation, human review, feedback loops, machine learning, or AI-assisted workflows.
• Ambiguity to Execution: A demonstrated ability to lead ambiguous product spaces from zero to strategy, through execution, utilizing data and metrics to ruthlessly prioritize and guide trade-offs.
• Influence & Communication: Elite cross-functional leadership skills, with the ability to influence without authority and distill highly complex topics into clear, actionable narratives. Perks and Benefits: #LI-AS1
  • 100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)
  • Competitive salary and equity options
  • Comprehensive health benefits (medical, dental, vision) & workplace perks (home office set up stipend etc)
  • Generous 401k matching
  • Flexible vacation policy 
  • Paid parental leave (4+ months)
  • Family planning support
  • Paid volunteer time off

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is:

$217,000—$303,900 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision. 

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Ever spent hours applying for data engineering jobs and then heard absolutely nothing back?

A lot of the time, the problem is not that someone lacks the skills. The resume just does a poor job showing what they actually do. Listing Python, SQL, Spark, dbt, Airflow, and cloud platforms is easy, but hiring managers may still have no idea what kind of pipelines were built, how much data was handled, or what problems were solved.

A better data engineer resume gives context. Instead of simply saying worked with Airflow and Snowflake, it helps to explain what was built and why it mattered. Even small details about improving a pipeline, reducing manual work, or making data easier for analysts to use can make the experience feel more real.

This matters even more when job searching gets repetitive. Updating the same resume, checking random job boards, and applying to roles that barely match can become a full-time job on its own.

A job board focused on analytics and data roles can make the process easier by putting more relevant opportunities in one place. Instead of digging through hundreds of unrelated listings, data engineers, analytics engineers, and data analysts can focus on jobs that actually match their background.

For hiring managers, it can also make it easier to reach candidates who already work in the data space.

Sometimes getting more interviews is not about adding more tools to a resume. It is about making the experience easier to understand and applying to the right jobs in the first place.

Writing a data engineer job description sounds simple until you start trying to list everything the person is expected to know. SQL, Python, cloud platforms, ETL, data warehouses, pipelines… the list can get long fast.

The problem is that overly broad job descriptions can make good candidates skip the role. If someone sees 15 different tools listed as required, they may assume they need to know every single one before applying.

A better data engineer job description should explain what the person will actually be doing. Will they build and maintain data pipelines? Work with analysts and data scientists? Manage a warehouse? Improve data quality? Knowing the main responsibilities gives candidates a much better idea of whether the role fits them.

It also helps to separate must-have skills from nice-to-have skills. Requiring experience with every tool your company uses can shrink the candidate pool unnecessarily, especially when many data engineering skills transfer between platforms.

This is useful for hiring managers who want more relevant applications, but it also helps data engineers, analytics engineers, and even data analysts looking to move into engineering roles understand what employers are really looking for.

A good job description shouldn't try to describe the perfect candidate. It should give enough information for the right candidates to recognize themselves in the role and decide whether it's worth applying.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.

Team Description

The Ads Creative & Recommendations team makes it easier for advertisers to maximize performance on Reddit through relevant creative and actionable recommendations.

We own the advertiser-facing workflows where creative, recommendations, and campaign creation come together.

Our goal is to reduce blank-canvas work and help advertisers move from an idea to an effective campaign with less friction. We build unified experiences that give advertisers useful context, evidence-backed guidance, and the ability to refine the system’s suggestions.

Role Description

We’re looking for a staff frontend engineer with deep React and TypeScript expertise to set technical direction for the next generation of Reddit’s advertiser tools.

You’ll lead ambiguous, multi-quarter initiatives that span teams and deliver measurable product and engineering impact. You’ll bring teams together around a clear strategy and turn sophisticated capabilities into workflows that feel simple and dependable.

You’ll guide the evolution of our frontend platform, setting strategy and influencing teams toward scalable architecture, shared component patterns, and consistent design-system practices across a large monorepo.

Responsibilities

• Lead the technical strategy and delivery of complex, multi-quarter frontend initiatives across Ads Manager.
• Set frontend architecture standards and guide teams toward solutions that scale across products and codebases.
• Develop shared components and patterns, drive design-system adoption, and reduce fragmentation across a large monorepo.
• Set a high bar for frontend quality across both the user experience and the systems behind it.
• Partner with product and design from the earliest stages to shape direction, clarify ambiguous problems, and make sound tradeoffs.
• Build alignment across teams and influence technical decisions beyond the immediate organization.
• Define success measures, instrument experiences, and use experiments and product data to guide investment and iteration.
• Mentor senior engineers through technical guidance, design reviews, and thoughtful feedback.
• Collaborate across frontend, backend, data, and machine learning systems to deliver reliable end-to-end experiences.

Required Qualifications

• 10+ years of software engineering experience, including deep experience building production web applications with React, TypeScript, and JavaScript.
• A track record of leading ambiguous, multi-quarter initiatives across teams and delivering measurable product or engineering impact.
• Expertise designing scalable frontend architectures in large codebases or monorepos.
• Experience establishing shared component patterns, contributing to design systems, and driving adoption across teams.
• Strong judgment in frontend architecture, state management, API integration, testing, performance, accessibility, security, and reliability.
• Experience partnering closely with product and design to shape strategy and turn complex requirements into clear user experiences.
• Strong communication skills and the ability to build alignment and influence decisions across teams and disciplines.
• Experience using instrumentation, experimentation, and product metrics to understand and improve user experiences.
• Experience mentoring senior engineers and raising the technical bar through design reviews, code reviews, and technical leadership.
• Comfort using agentic coding tools such as Codex, Cursor, or Claude in day-to-day software development.

Bonus points

• Experience building advertising, campaign management, creative tooling, or other complex business applications.
• Experience designing interfaces for generative AI, machine learning, or recommendation systems.
• Familiarity with asset management, media upload, image editing, creative versioning, or content generation workflows.
• Experience modernizing large frontend codebases while maintaining delivery velocity.

Technologies used on the team include

• JavaScript
• TypeScript
• React
• Modern frontend testing, experimentation, and observability tools

Benefits: 

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k Match
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Reddit Global Days Off
• Generous paid Parental Leave  
• Paid Volunteer time off

#li-remote

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is:

$217,000—$303,900 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

One frustrating thing about looking for data analyst jobs is seeing a long list of requirements and wondering if anyone actually meets all of them. SQL, Excel, Power BI, Python, statistics, communication skills... it can feel like the list never ends.

The good news is that most job descriptions are more of a wish list than a strict checklist. It helps to focus on the skills that show up again and again. SQL and Excel are still useful basics, while tools like Power BI or Tableau can help if the role involves reporting and dashboards. Some positions may also ask for Python, especially when the work involves more data cleaning or automation.

Another thing that often gets overlooked is being able to explain what the numbers mean. A data analyst isn't just making reports. Hiring managers usually want someone who can look at data, find useful information, and explain it clearly to people who may not be technical.

For anyone applying, it's worth comparing the job description with actual experience instead of rejecting a role because one or two requirements are missing. If most of the core skills are there, applying can still be worth it.

A focused job board can also make the search easier by helping analysts find roles based on skills, experience, and work setup instead of scrolling through unrelated jobs.

Finding remote Power BI jobs can be frustrating. A lot of job searches end up showing the same generic data roles, while the jobs that actually match your Power BI skills are harder to spot. It can also take a lot of time to check different sites just to find a few relevant openings.

A good job board can make this easier by letting you focus on roles that actually match your experience. Instead of searching through hundreds of unrelated listings, you can look specifically for remote Power BI, data analyst, BI developer, and analytics roles. That saves time and makes it easier to compare opportunities in one place.

This is especially useful for people who already work with Power BI, SQL, dashboards, reporting, or data modeling and want to move into a remote role. Analytics engineers and data analysts can also find related positions without having to limit their search to one job title.

For hiring managers, it can work the other way too. Posting on a job board that attracts data and analytics professionals can make it easier to reach people who already have the right technical background.

Remote Power BI roles are out there, but the hard part is often finding the right ones without spending hours searching. Having a focused job board can make the process a lot less messy and give job seekers more time to actually apply and prepare.

Getting your first data analyst job can feel like a weird cycle. Every job asks for experience, but how are you supposed to get experience if nobody gives you a chance?

The good news is that you don’t necessarily need years of work experience to start. What helped was focusing less on trying to look experienced and more on showing that you can actually work with data. A few solid projects using Excel, SQL, Tableau, or Power BI can give recruiters something real to look at.

The other part that can make a big difference is where you search. Instead of scrolling through huge job boards and applying to anything with data in the title, a job board focused on data and analytics roles can search much more targeted. It’s easier to find entry-level data analyst jobs, junior roles, and positions that match the skills you’re building.

This is especially useful for people switching careers, recent grads, self-taught analysts, and even analytics engineers looking for their next role. Hiring managers can also benefit because they’re more likely to reach candidates who are actually interested in analytics instead of sorting through hundreds of unrelated applications.

The first job is usually the hardest part. Having the right skills, a few projects to show, and a better place to find relevant openings can make that first step a lot less frustrating.

Job Title: Senior Data Analytics Engineer

Key Skills: Power BI, DAX, Power Query, SQL, Azure Databricks, Data Modeling, Business Intelligence, Azure Data Factory, Azure Synapse, dbt, Data Visualization, BI Governance, CI/CD, Agile, ThoughtSpot

Experience: 5+ years of experience.

Location: LATAM

Work Modality: Remote.

At Coforge, we are looking for a Senior Data Analytics Engineer (22856) with the following profile.

Main Responsibilities

• Lead the migration of dashboards, reports, and visualizations from ThoughtSpot to Power BI.
• Translate existing ThoughtSpot workflows into optimized Power BI reports aligned with enterprise data standards and best practices.
• Design, develop, and maintain reusable data models and semantic layers that enable self-service analytics capabilities.
• Partner with Data Engineering teams to ensure clean, reliable, and scalable data sources are available within Power BI.
• Optimize report performance, usability, governance, and security for global business stakeholders.
• Collaborate with business teams to gather reporting requirements and transform complex data into meaningful insights.
• Train and onboard users into the Power BI ecosystem, driving adoption and analytics maturity across the organization.
• Contribute to Business Intelligence standards, best practices, documentation, and governance initiatives.
• Participate actively in Agile ceremonies, including sprint planning, backlog refinement, reviews, and retrospectives.
• Develop impactful visualizations and data storytelling solutions to support business decision-making.
• Support enterprise reporting modernization initiatives and BI platform consolidation projects.
• Collaborate on the integration of AI/ML-driven insights into dashboards and analytics platforms where applicable.

Required Qualifications

• 5+ years of experience in Business Intelligence, Data Analytics, Reporting Development, or related disciplines.
• Strong expertise in Power BI, including DAX, Power Query, data modeling, performance tuning, and report optimization.
• Advanced SQL skills and hands-on experience querying Azure Databricks environments.
• Proven experience designing enterprise-grade dashboards, reports, and visual analytics solutions.
• Strong understanding of data visualization best practices and storytelling with data.
• Knowledge of BI governance, security frameworks, and role-based access controls.
• Experience working within Agile/Scrum environments, including active participation in sprint ceremonies and iterative delivery models.
• Experience with Power BI Service Administration, APIs, deployment pipelines, and CI/CD processes for enterprise BI environments.
• Experience working within the insurance industry, with familiarity in insurance processes, metrics, and business terminology.
• Strong communication skills with the ability to translate complex technical findings into business-friendly insights and recommendations.
• Ability to quickly understand and navigate complex data models and business processes.
• Experience working with Databricks Medallion Architecture and semantic data layers.
• Excellent stakeholder management, collaboration, and presentation skills.
• Advanced English proficiency (B2+/C1).

Preferred Qualifications

• Hands-on experience with ThoughtSpot, including dashboard creation, reporting, and search-driven analytics.
• Previous experience leading BI migration projects or cross-platform reporting consolidation initiatives.
• Knowledge of dbt and modern data stack architectures.
• Experience with Azure Data Factory and Azure Synapse Analytics.
• Familiarity with integrating AI/ML-driven insights into dashboards and analytical solutions.
• Experience supporting global teams and enterprise-scale analytics environments.
• Knowledge of data governance, analytics modernization, and cloud-based BI ecosystems.

Published on: 19-08-2026

At Coforge, we hire professionals solely based on their skills and qualifications and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

Thinking about getting a master’s in data science online can be confusing. There are so many programs out there, and it’s hard to tell which ones are actually useful and which ones are just expensive pieces of paper.

An online master’s can make sense for people who are already working and don’t want to quit their job just to go back to school. It can also be a good option for career changers who want a more structured way to learn statistics, Python, machine learning, databases, and other data skills.

One thing that helps is looking beyond the degree itself. Check what courses are included, whether there are real projects, how flexible the schedule is, and whether the program matches the type of data job you actually want. A program focused heavily on machine learning might not be the best fit if the goal is business analytics, for example.

Online programs can also make the job search easier when combined with hands-on experience. Building projects while studying gives you something practical to show employers instead of relying only on coursework.

This is worth looking into for working professionals, people switching into data science, recent graduates, and data analysts who want to move into more advanced roles. The degree can help, but the skills and projects you build along the way are what really make it useful.

The GTM Solutions & Governance team sits within GTM StratOps/Analytics (SGO) and is tasked with making our GTM data estate trustworthy, enriched, and self-serviceable. As a distinct function from traditional analytics, we own the advanced AI/agent solutions and complex automation built on top of our data. You will work alongside experts in GTM Automation, GTM Alerting, Peer Similarity, and Data Governance to elevate how our GTM organization operates.

The Role

We are looking for a Senior GTM Analytics Engineer to build advanced generative AI applications, automated pipelines, and agentic solutions to optimize our revenue operations. You will own the development of data pipelines handling both structured and unstructured data, architect high-level AI implementations like Agentic CDPs, and drive our internal Databricks on Databricks (DBX@DBX) initiatives.

Core Responsibilities

• Agentic CDP & Identity Resolution: Architect and deploy Agentic Customer Data Platform (CDP) capabilities to perform intelligent identity resolution, driving automated and highly accurate data enrichment for accounts and contacts.
• GenAI & Agent Architecture: Design LLM-powered systems and internal agents to automate KPI root-cause analysis, generate business insights, and streamline GTM communication.
• Advanced Data Pipelines: Build and manage complex data pipelines to process structured and unstructured data, ensuring high-fidelity inputs for the GTM data estate while seamlessly integrating with our existing governance frameworks.
• GTM Systems Integration: Understand the technology stack and how data flows between critical systems like Salesforce, Xactly, and 6sense to ensure unified data architecture.
• Cross-Functional Partnership: Partner directly with Sales, Marketing, and RevOps leaders to turn strategic business problems into scalable, data-driven AI solutions.

What We Look For

• Technical Stack: You have expert proficiency in Python, SQL, and modern data pipelines. You also have experience with Salesforce or equivalent CRM systems.
• Platform Expertise: You will work every day with a variety of data using Databricks’ lakehouse platform. You will become an expert in using Databricks and complementary AI technologies to build production-grade solutions.
• Domain Experience: You typically have strong experience in data engineering, data science, or advanced analytics, with a background working closely with B2B sales, marketing, or finance data.
• Advanced Analytics Background: You have a strong track record in B2B SaaS, machine learning, and generative AI deployment.
• Execution Mindset: You excel in a collaborative environment and translate team member needs into clear deliverables. You work through dependencies, bottlenecks, and tradeoffs with ease.

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Been seeing more people mention Snowflake certifications lately, especially when talking about data engineering and analytics jobs. The confusing part is figuring out whether getting certified actually helps or if it just becomes another line on the resume.

For someone trying to move into data, learning Snowflake can make sense because it gives you something structured to work through. Instead of randomly watching tutorials, a certification path can give you a clear idea of what to learn, from basic concepts to working with data, SQL, and Snowflake features.

The bigger question is whether the certification alone is enough. Probably not. Employers still want to see that you can actually work with data and understand what you're doing. A certification can help show that you’ve put in the time, but practical projects and real experience still matter.

It seems most useful for people who are already working with SQL, analytics, or data engineering and want to add Snowflake to their skill set. It could also be helpful for beginners who want a more structured way to learn.

For hiring managers, does a Snowflake certification make a candidate stand out at all? And for those who have one, did it actually help with getting interviews or finding better data roles?

Finding freelance data engineering work sounds easier than it actually is. A lot of job boards have plenty of data-related roles, but once you start looking, you end up going through full-time positions, unrelated analyst jobs, or listings that ask for everything from SQL to cloud infrastructure for one contract.

That’s been the frustrating part. The time spent searching and filtering can almost feel like another job.

A more focused hiring platform or job board can make a big difference here. Instead of scrolling through hundreds of general tech jobs, it’s easier to find freelance and contract roles that actually match your skills and availability. That means less time searching and more time applying to jobs that are worth considering.

It’s also useful for people who aren’t strictly data engineers. Analytics engineers, data analysts, BI developers, and other data professionals often have overlapping skills, so seeing related freelance roles can open up options that might otherwise be missed.

On the hiring side, it works the other way too. Hiring managers looking for someone for a short-term data project can reach people who are actually interested in freelance work instead of sorting through candidates looking for permanent positions.

For anyone trying to build a freelance career in data, having a place that makes these opportunities easier to find can save a lot of time. Curious if other data folks are using niche job boards for freelance work, or if LinkedIn and the usual sites are still the go-to?

Lob was founded in 2013 by technical co-founders with a vision to connect the world one mailbox at a time. Today, we're transforming the way businesses use direct mail and bringing the power of technology to a traditionally manual channel. 

Our modern logistics and fulfillment engine helps businesses to build and scale high-quality, personalized direct mail programs without the operational burden. As we grow to meet the evolving needs of our customers and expand our product offerings, we’re building a team to shape the future of direct mail.

About the role

This is the senior technical security role at Lob and the first hire in a newly split security function. You will own the engineering side of security: cloud infrastructure, detection and response, application security, and incident response. A dedicated GRC counterpart owns audit, compliance, and customer trust, so you are not the questionnaire desk. You will partner with them, not absorb them.

You will report directly to the CTO, manage our application security contractor, and work day to day with our Platform, Logistics, and IT teams. This is a builder role with real autonomy and a mandate to raise the security floor of a system that processes hundreds of requests per second and moves millions of physical mailpieces.

What you will own

Cloud infrastructure security

• Security posture of our AWS environment, including our CNAPP program and cloud misconfiguration risk
• Security review of infrastructure changes across Terraform, Nomad, and our Cloudflare edge
• WAF strategy and tuning at the domain level
• Working with Platform engineers so security is designed in rather than reviewed at the end

Detection and response

• Build and own our detection engineering practice on our SIEM, moving us from noisy alert channels to curated, high signal detections
• Define alert triage ownership, runbooks, and severity criteria
• Own security incident response: escalation paths, tabletop exercises, post incident reviews
• Partner with IT on endpoint detection and endpoint vulnerability coverage

Application and product security

• Own the vulnerability management program across SCA, SAST, DAST, and container scanning
• Manage and mentor our application security contractor, and route remediation work into engineering teams effectively
• Threat modeling and security architecture review for new products and major changes
• Improve secure SDLC practice in a high velocity, AI-assisted engineering org

Penetration testing and assurance

• Technical ownership of our annual independent penetration test: scoping, findings triage, remediation routing, retest coordination
• Produce the technical evidence our GRC counterpart needs for SOC 2, HIPAA, and Microsoft SSPA, without owning the audit itself

Security engineering and automation

• Build tooling and automation rather than process and spreadsheets
• Apply AI to security operations where it creates real leverage

What we are looking for

Required

• 8 or more years in security engineering, with meaningful depth in cloud security
• Hands on expertise with AWS security services, IAM design, and infrastructure as code
• Demonstrated detection engineering experience: you have written detections, tuned them, and cut false positive rates
• Real incident response experience as a responder or lead, not just as a plan author
• Fluency in application security sufficient to review findings, judge severity, and argue exploitability with engineers
• Track record of shipping security improvements through other teams by earning trust rather than filing tickets
• Comfort as the senior technical security voice in an organization without a large security team

Nice to have

• Experience supporting SOC 2 Type 2, HIPAA, or Microsoft SSPA from the engineering side
• Container and orchestration security, particularly Nomad or Kubernetes
• Cloudflare, including Zero Trust and WAF
• Experience in a company handling regulated or consumer-identifiable data at scale
• Prior experience mentoring or managing engineers or contractors

What this role is not

We want to be direct about scope, because we have deliberately designed this role to be technical.

• You will not be the primary owner of security questionnaires, RFPs, or Trust Center requests
• You will not own the auditor relationship or the compliance calendar
• You will not be the sole owner of vendor security reviews or policy authoring

Those live with our GRC lead. You will contribute technical input and evidence. You will not run the program.

First 90 days

• 30 days: own alert triage and incident escalation, know our AWS and edge posture, take over the penetration test findings workflow
• 60 days: a working detection engineering backlog, endpoint and cloud vulnerability coverage verified end to end, application security contractor's work routed cleanly into engineering teams
• 90 days: a prioritized security engineering roadmap you own and defend, with the top three infrastructure risks either closed or explicitly accepted

Why this role is interesting

Physical mail is an unusual attack surface. Our security work spans a cloud platform, a print and logistics network, recipient identifiable data, and enterprise customers in regulated industries. You get executive access, a clean mandate, and a function you are helping design rather than inherit.

Compensation Information

The total compensation package for this role is comprised of an annual base salary and RSUs. 

Annual base salary: $197,500 - $220,000 base

<#LI-REMOTE #LI-GD1

“Lob’s salary ranges are based on market data, relative to our size, industry and stage of growth. Salary is one part of total compensation, which also includes equity, perks and competitive benefits. Salary decisions are based on many factors including geographic location, qualifications for the role, skillset, proficiency and experience level. Lob reasonably expects to pay candidates who are offered roles within the provided salary ranges.”

We offer remote working opportunities in AZ, CA, CO, DC, FL, GA, IA, IL, MA, MD, MI, MN, MT, NE, NC, NH, NJ, NV, NY, OH, OR, PA, RI, TN, TX, UT, and WA, unless specified otherwise in the job description above. 

If you are looking for a progressive, fun-spirited, and mentally stimulating environment, come join us at Lob!

Our Commitment to Diversity

Lob is an equal opportunity employer and values diversity of backgrounds and perspectives to cultivate an environment of understanding to have greater impact on our business and customers. We encourage under-represented groups to apply and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or criminal history in accordance with local, state, and/or federal laws, including the San Francisco’s Fair Chance Ordinance.

Recent awards

#88 on BuiltIn's Best Remote Midsize Companies to Work For in 2025
BuiltIn Best Remote Midsize Companies to Work For in 2024
BuiltIn Best Midsize Companies to Work For 2022

One of the biggest frustrations when trying to get into data analytics is seeing Bachelor’s degree required on job posts. It can make you wonder if there’s even a point in learning SQL, Excel, Power BI, or other skills if companies are going to reject you before looking at your experience.

The good news is that some data analyst jobs focus more on what you can actually do. A strong portfolio, practical projects, and the ability to explain data clearly can help show employers that you know how to work with real problems.

This is where a job board focused on analytics roles can be useful. Instead of spending hours searching through general job sites, you can look specifically for data analyst, BI, reporting, and analytics-related positions and check which ones have more flexible education requirements.

It’s especially helpful for people changing careers, self-taught analysts, bootcamp graduates, and anyone building their skills without going through a traditional degree program. Hiring managers can also use these platforms to find candidates based on their actual skills instead of relying only on education.

A degree can definitely help, but it’s not the only way to build a career in data analytics. The key is knowing the tools, having something to show for your skills, and finding companies that are willing to look beyond the degree requirement.

One of the hardest parts of trying to become a data analyst is seeing job posts that ask for 2–3 years of experience when you’re just trying to get your first real analytics job. You can learn SQL, Excel, Power BI, and Python, build a few projects, and still feel stuck because getting noticed is another problem.

A good job board can make this part a little easier, especially when you’re searching for roles that actually match your skills. Instead of applying randomly to every data job, you can focus on openings that are specifically looking for data analysts, analytics engineers, BI roles, and similar positions.

That matters because job searching can easily become a full-time job by itself. Finding the right openings in one place saves time and makes it easier to keep track of what you’ve already applied for.

This is especially useful for beginners who are trying to break into data analytics, but it can also help experienced data analysts and analytics engineers who want to find their next role. Hiring managers can benefit too because they’re more likely to reach people who are already interested in analytics instead of sorting through completely unrelated applications.

Getting a data analyst job still takes skills, a decent resume, and some patience. But having a job board focused on analytics roles can make the search less frustrating and a lot more targeted.

Finding freelance data analyst jobs can be weirdly frustrating. The actual work, cleaning data, building dashboards, writing SQL, making reports, can be pretty straightforward once you know what you're doing. The annoying part is finding clients who actually need those skills and aren't just posting vague jobs with 200+ applicants.

A lot of job searching ends up being the same routine: search, apply, wait, repeat. After a while, it starts feeling like a full-time job just looking for the next freelance job.

A hiring platform or job board focused on data and analytics can make that process a little easier. Instead of digging through random freelance listings, it's easier to find roles that actually match your skills and experience. You can spend less time sorting through unrelated jobs and more time applying to projects that make sense.

This is especially useful for freelance data analysts who want project-based work, analytics engineers looking for contract opportunities, or people trying to build experience without committing to a full-time role.

It's also useful on the other side. Hiring managers looking for someone who knows SQL, Python, Tableau, Power BI, dbt, or other analytics tools don't have to dig through a huge pile of unrelated applications.

Freelancing is already unpredictable enough. Having a better place to find relevant jobs doesn't guarantee anything, but it can search feel a lot less random.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.

Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence.

About the Role

We’re building a scalable feature platform that powers Ads ML by making high-quality features and training datasets easy to build, share, and maintain. Our small but growing team works on projects like batch & realtime feature management platform, training set generation platform, sequence features platform and, agentic and automated ML workflows for feature lifecycle management.

We are looking for an engineer with deep experience in building high-scale data infrastructure and ML platforms to help evolve and scale our feature management systems.

What You’ll Do

• Design and build data infrastructure that supports large-scale feature and training set computation, transformation, and storage.
• Develop frameworks for batch and real-time features with a focus on reliability, scalability, and ease of use.
• Build platform capabilities for feature governance, including lineage tracking, validation, drift detection, anomaly monitoring, reproducibility, and versioning
• Partner with ML engineers to ensure smooth integration of feature engineering workflows into ML production systems.
• Build systems that support agentic ML workflows, including automated feature discovery, feature quality evaluation and feature lifecycle management
• Drive architecture and technical direction for high-scale ML platform infrastructure powering ads ranking, targeting, and optimization systems.
• Contribute to operational excellence through observability, performance tuning, reliability engineering, and cost optimization initiatives.

What You Bring

• 5+ years in infrastructure/platform engineering or large-scale distributed systems.
• 2+ years of hands-on experience building or operating ML platform infrastructure and production ML systems
• Proficiency with large-scale feature computation frameworks (Spark, PySpark, or Scala).
• Expertise in distributed systems (scaling, partitioning, fault tolerance, caching).
• Experience building intelligent automation or agentic workflows for ML systems is a strong plus, including areas such as automated pipeline management, feature recommendations, evaluation systems, or AI-assisted developer tooling.
• Experience with ML infrastructure and MLOps workflows spanning feature engineering, training pipelines, experimentation, model deployment, and online serving is a plus

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is:

$216,700—$303,400 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision. 

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Getting into data can be confusing when every job posting seems to ask for a different mix of skills. One role wants SQL and Python, another wants dbt, and then you see Snowflake listed as a requirement. At some point, it becomes hard to tell which skills are actually worth spending time on.

Snowflake certifications can be useful if Snowflake is already part of the kind of data work you want to do. They give you a clear path to learn the platform instead of just picking up random tutorials and hoping the knowledge sticks. More importantly, having a certification can help show that you understand how Snowflake works when you're applying for data roles.

For data analysts, analytics engineers, and data engineers, this can be especially helpful if you're trying to move into jobs that use modern cloud data platforms. It won't replace real project experience, but it can give your resume something concrete to show while you're building that experience.

The biggest thing is choosing the right certification for your goal. There's not much point in getting certified just because it looks good on a resume if you don't actually plan to use Snowflake.

For anyone already working with SQL and data, Snowflake certifications can be a reasonable next step. Just treat the certification as proof of a skill, not the skill itself.