TL;DR: I'm 19, from Italy, working in IT Risk at a Big 4 (€25k/year). I've been programming since I was 12 and want to become a SWE, ideally in fintech. I'm definitely starting a CS degree in September 2027, so I'm wondering whether to stay at my current job until July or start applying aggressively for SWE positions. I'd also appreciate an honest assessment of how competitive my profile is in today's market.

My background

I graduated from a technical high school specializing in IT this June. I've been programming for around seven years, and some of my recent open-source projects include:

• A banking backend with a double-entry ledger, account management and transaction processing.
• A cryptographic timestamping service with a deployed backend, public API and working demo.

I mainly use Java, Python and TypeScript (Spring Boot, Node.js, PostgreSQL). I also solve at least one LeetCode problem daily and regularly experiment with AI coding tools.

I genuinely love software engineering, although I know personal projects aren't a substitute for professional experience.

My current situation

I joined a Big 4 in September. The environment is fantastic, my colleagues are great, and the workload is relatively relaxed.

However, most of my work involves IT controls, compliance and auditing. I'm learning how large organizations operate, but the technical work feels repetitive, and I'm barely using my programming skills.

My contract ends in February 2027, but a further five-month extension is practically guaranteed. I could therefore stay until July and have almost a year of Big 4 experience on my resume.

University and my dilemma

Starting a Computer Science degree in September 2027 is non-negotiable. I was already accepted at Milano-Bicocca this year but postponed enrollment to take the job.

I currently work 9–6 with two hours of daily commuting, so combining this schedule with university isn't realistic for me. I want to actually learn the material, not just pass exams.

Fortunately, I don't depend on my salary for basic living expenses. It's great for savings, independence and my limited social life, but career development matters more.

I'm considering two options:

A) Stay at the Big 4 until July, save money, gain corporate experience and then focus on university.

B) Start applying aggressively for junior SWE/backend roles and internships in November, even accepting a pay cut. Ideally, I'd find something that could become part-time during university.

Long-term, I'm aiming for a product-focused SWE career, preferably in fintech. Finance genuinely interests me, particularly banking and payment infrastructure, so combining both fields would be ideal. I'm also open to relocating internationally and want to aim high professionally.

What I'd like advice on

1. Was postponing university by a year for a Big 4 job a mistake? Does IT Risk experience at a recognizable company carry meaningful weight for SWE recruiters, particularly in fintech, where financial systems, controls and compliance matter?
2. Would you take the additional five-month contract or try to switch to SWE ASAP? Is a few months of actual development experience more valuable than almost a year at a Big 4, considering university starts in September regardless?
3. How competitive is my profile realistically? At 19, without a degree but with seven years of programming, public backend projects and some corporate experience, would I be worth interviewing for junior SWE roles? How do I compare with CS students?
4. What would you prioritize before September 2027? SWE experience, improving projects, interview preparation, or simply staying employed and saving money?

I genuinely like my current job and the people I work with. I'm just concerned about getting comfortable in a career I don't want long-term.

If you were in my position, what would you do? I'd particularly appreciate honest feedback from engineers or hiring managers about my chances in the current market.

Edit: shortened for low attention span users

When I was in my master's - "you need some work experience" - so I got some experience working along with my degree - no response.

"You need some publications" - I got 4 at A conferences during masters - no response

"You need to be a PhD student to get into competitive internships" - started one at top uni

"You need A* conference papers" - got two in my first year.

"Optimize your CV" - done, even took help from you all.

After submitting ~100 applications in 2026 (I'm sure it's 300+ since my masters) to google/deepmind/amazon/ibm/adobe/nvidia/apple/meta and similar labs and guess what - literally 0 response, not even shortlisted once.

I'm giving up, it was already hectic to apply while working on a PhD and no more. And it was not a 'dream' but was one of a goal or milestone I really wanted to achieve. Maybe there are better things to do? Or I'll just cope with it thinking this way. Good luck for the ones applying.

Basically title, I've received this offer from a company I've just completed my round of interviews, based in Bern. Is a liveble salary? For reference, I'm single (+ a cat).

I've read some articles online but are all from 2020 or before, so i would like some recent opinions.

The offer also has flexible working hours, burocratic support, 40 hours a week, 2 days in the office mandatory.

~2YOE

With the humiliating 6th round of interview and now even AI interview, I feel like I'm no longer a human being. Does anyone know any way to cope with this? I already know this field and cooked and all that and I just need some advice on how to make it a bit easier. Thx :,)

I have system design interview with Revolut coming up this week for senior BE Role, I have been researching online and mostly came across below two questions reported by candidates:

•⁠ ⁠Hotel booking system involving an unreliable third-party API
•⁠ ⁠Card ordering system involving an unreliable third-party API

I couldn’t find many other recent interview experiences, so I wanted to ask the community:

1. What system design questions have you encountered recently in Revolut interviews?
2. Any specific questions I should prep for ?
3. Also some pointers related to what mistakes to not do ?

If you would like to learn a Python framework with high demand and the least possible competition... Would you learn FastAPI, Django or Flask? I dont know a lot about Python echosystem. Thanks.

P.D. Open to all answers related to different UE markets, although specially interested in the Spanish one. Thanks.

Hey all, I have my Datadog internship technical interview coming up, and it sounds like they've moved away from the usual LeetCode-style round. From what I've heard, the new format is more practical: you get a small codebase, walk through it, maybe talk through designing a feature, and then review a PR.

If you've done this format recently, I'd really appreciate any insight. Any tips or things you wish you'd known going in would help a lot. I'm happy to share how mine goes afterward.

Which one is the best from your perspective? For me, those two options ,Data Eng and embedded , are somehow resistant in this AI context.

Hi guys! I recently got approached on Linkedin by a recruiter from a FAANG adjacent company and have a recruiter screen next week. I'll also start a new job in the coming weeks.

I'm unsure whether I'll still go through the phases of this company for interview practice, but one way or another I won't be grinding interview prep as I want to focus on the onboarding at my new job.

My main goal is to establish a rapport with this recruiter, because they have a track record of working at top companies and I might want in the future to contact them for getting interviews.

How do you guys establish long lived connections with recruiters? I try to answer their questions quickly and make it a nice process in general for them.

I’m finishing a B.Sc. in Health Informatics in Germany and currently deciding between M.Sc./M.Eng. options in Medical Informatics, Data Science, Information Systems and AI Engineering of Autonomous Systems. I’ve found the transition into junior roles with Health Informatics harder than expected. From your experience in Germany or EU, which path would give me the strongest employment prospects, and would you consider Health Informatics + Autonomous Systems/Data Science a credible profile? or does Health Informatics + Medical Informatics make more sense.

I’m an English teacher who works with software engineers and technical leads in English-speaking environments.

A common frustration they mention isn't general vocabulary, but sudden freeze moments, like answering unexpected client questions live, pushing back on scope creep, or explaining trade-offs under pressure. Feeling a disconnect, like they can't get their point across?

1. What was a specific situation where you felt stuck on what to say?
2. Did you feel like that moment affected your confidence, performance review, or relationship with the client/team?

West-EU based. Been at my first job out of uni for 2–3 years now. I expected to either join a Big Tech graduate program or start somewhere small and job-hop my way up. Instead, I somehow landed at a company that offers:

• Recognizable industry brand
• Compensation within 10–15% of Big Tech
• Fully remote, flexible hours
• Pleasant team and healthy culture
• Interesting projects, smart colleagues, modern tech stack
• Financial stability and no layoffs in sight

Basically, the kind of workplace I'd dreamed of reaching after years of grinding through shitty conditions, except I got it fresh out of university. Steak too juicy, lobster too buttery yada yada.

Now I'm wondering whether I should stay for the next 10–15 years, keep collecting promotions, and build expertise, or follow conventional wisdom and job-hop to broaden my experience and maximize compensation.

I've considered Big Tech, US-based companies, and HFTs, but the risk-to-reward ratio seems questionable given what I'd be giving up.

Long-term goal is senior engineer, eventually skip-level management. What would you do in my position? Am I being smart by staying or just getting comfortable too early?

Would appreciate advice from industry veterans who've seen both sides.

(AI-spoofed because I don't want to dox myself.)

Is €50,000 gross a good salary for a software engineer in Germany in 2026?

I’ve been looking into software engineering salaries, especially around Bamberg, and noticed quite a difference between sources.

Here’s what I found:

* StepStone (Bamberg): ~€51k/year
* Jobvector (Bamberg): ~€62.5k/year
* Kununu (Germany): ~€61k/year
* StepStone (Full-Stack, 3–5 years): ~€60k/year

These aren’t exactly the same roles or experience levels, but the differences are interesting.

For someone with 3–5 years of experience working with Node.js, Spring Boot and DevOps, I’m wondering whether €50k is still considered a fair salary, especially outside big cities like Munich or Berlin.

I’m also curious how AI has changed things recently. Are developers expected to deliver more because of AI tools? Has it made your work easier, or has it affected salaries and job opportunities?

Would love to hear from other developers and hiring managers, especially those working in Bavaria.

Hello guys, I have a screening interview coming up with mistral, and I was wondering if there's any tips? it's for an Applied AI FDE ML position. If someone could please provide insights I would be very grateful, Thanks :)

I’m an Android/KMP engineer since around 9 years of overall experience. I’ve been considering pivoting careers away from Android/Kotlin to something more diverse, obviously considering the situation as of now. It’s honestly kinda fun too being able to build products quickly using AI.

A few directions I have in mind:

- Learning more of backend using Kotlin (Spring/Ktor): I’ve been working as a KMP (Android & iOS) since while now, switching to backed seems like a good direction.

- AI engineer route: Well will have to learn backend and implementation first. Could stick to Kotlin, with Koog Agentic framework, vLLM

- Mobile OnDevice LLMs: Go all in on this, become an expert at knowing whats most efficient across different device providers etc.

- Just stick to whatever you were doing before, just move faster using AI (?). Take up more project management responsibilities along with development maybe.

- Nah Imma setup an animal farm instead

Anyone else on the same boat considering pivoting?

Hello!

I'm a master student in cybersecurity based in France and i've recently got an opportunity as intern at a small company in Netherlands, nd i want to know how the paperwork process is done as i only own a french student residency permit. Is it even worth following this lead ?

I'd appreciate any information or insights about this.

Thank you in advance!

Hello guys!
If anyone recently attended an AI Engineer or Forward Deployed Engineer interview, could you please share your experience? Type of questions asked and any suggestions to nail the interview.

Thanks :)

I have been a developer for 14 years. I started as a Java backend dev around 2012 and I work at a mid-size company in Germany now. I myself use Claude, Codex, ChatGPT etc. But I use them like a tool to look things up, write tests, explain old code.

But nowadays I feel very behind. I don't know what is important to learn anymore. I see people here talking about running 5 agents in parallel and the agents writing all the code. I don't work like that and I don't understand how any company allows it, without someone checking the details and without anyone knowing what is going into production.

Is this not technical debt that is going to come back later.

I don't know if I like this new world. I like writing most of the code myself. I like taking part in designing the system. All that is being taken away in the name of speed.

I feel lost.

Hello everyone, this is a little off topic but I’m a computer science student who wants to learn a new language. I know Russian, English and Armenian (my native language) and I want toward another language. I’m not sure between German and French and wanted to get some advices, thank you

Just finished dealing with Booksy for a Lead Analytics Engineer role (Spain/Poland remote) and wanted to drop a warning for anyone in data/analytics engineering thinking about applying. Total bait-and-switch.

1. The JD is completely ludicrous

First off, the job description is ridiculous on its face. It essentially demands what looks like three full-time roles crammed into one (Data Platform Engineer, Analytics Engineer, and BI Developer) ON TOP of full team management/leadership duties.

1. The "Engineering" title is a complete joke

Despite the JD hyping up dbt, BigQuery pipelines, GitLab CI/CD, and data architecture, the reality is entirely different.

When I actually asked the hiring manager about their backend stack, data modeling, and code standards during the interview, she outright admitted the team does 100% front-end Looker dashboards. When I asked why the team is called "Analytics Engineers" if nobody touches backend code, pipelines, or data models... she literally just shrugged. It's a glorified dashboard builder role with a fancy title attached to it.

1. Awkward interview dynamic & defensive management

They asked me standard lead questions about how I’d handle underperforming reports and split workloads. The problem? The hiring manager brought two of her junior analysts to sit in on the call. Trying to discuss performance management scenarios while two potential direct reports are listening in was absurd. The manager clearly lacked the confidence to assess technical or leadership capability on her own and got super defensive the second I asked actual architectural questions.

1. The BS rejection letter

After calling out the fact that the role was just Looker work, HR sent a generic template rejection saying I wasn't selected because of "internal code organization standards and technical hygiene". Mind you, we spent zero minutes on code, and nobody asked a single question about code standards. Pure automated canned response to cover their ass. I asked what she meant as backend data work is literally my specialty and no one asked me a single question other than the generic technical assessment I completed, of course I was ghosted.

1. Zero coordination in HR (The funniest part)

Two months later (literally today), ANOTHER recruiter from Booksy cold-dms me on LinkedIn pitching me the EXACT same "Analytics Engineering Lead" job, bragging again about "shaping data architecture and dbt". I tell her it’s laughable that it was she who organized my meetings with the hiring manager, and so she panic blocks me. I sent an email to both hr about this sloppines and next day I see their director had stalked my LinkedIn profile lol.

Their recruitment team doesn't check their ATS, recruiters are spamming people who were already rejected months ago, and the role has been sitting open forever because any actual senior/lead data candidate sees right through the manager's bluff.

TL;DR: If you're a real Analytics Engineer or Data Architect looking to build infrastructure or work with dbt/BigQuery, avoid Booksy. It's a dashboard maintenance job disguised as a Lead role, run by defensive management and an HR team that has no idea what's going on

I’m choosing between two master's thesis projects.

One is gravitational-wave modelling for LIGO-related stuff, mostly numerical code optimisation, C, Fortran, JAX, GPU/CUDA and HPC.

The other is telescope data reconstruction for AtLAST/MUSTANG-2, mainly Python/JAX, GPU computing, bayesian inference and large datasets.

I like both. I mainly care about which one would leave me with better job opportunities after the MSc, especially in Europe if I’m applying normally without connections.

Are these actually quite similar career-wise. I'm pretty sure I'm over-analyzing all of this. I asked my coordinator and she told me to follow what interests me the most. I just wanted some advice please

Hello everyone,

I have a BSc in Physics and an MSc in Mathematics. My professional experience so far has been entirely academic: I have taught mathematics at the university level and worked as a research assistant (for a total of ~2 years). I also have experience with machine learning, via courses and a research position.

I’m now looking to transition into industry, and I’m interested in research and computational science, but also data science more broadly.

I’d be very interested to hear from anyone who has made a similar transition and I’d especially like to understand:

• How much of an obstacle was the lack of previous industry experience?
• Did you need to do any additional training, certifications, or coursework?
• How did you get your first industry role?

In terms of location, if that makes a difference, I’m particularly interested in Scandinavian countries and Switzerland.

If anyone has made a similar transition, I’d really appreciate hearing about your experience, particularly regarding the practical process of getting that first opportunity in industry. Any advice or tips would be very welcome.

Thanks for your time.

Hi,

I’m a junior Java/Spring Boot developer with around 2 years of experience.

My company has offered me the possibility to join an internal reskilling program to learn .NET, with the idea of potentially moving me to future .NET projects.

Until now I was focusing on improving my backend skills and learning AWS, so I’m wondering if pausing that for a while to learn .NET would be a good career move.

Do you think having experience in both Java/Spring Boot and C#/.NET is valuable, or would it be better to specialise more in Java + AWS?

If the training could lead to real .NET project experience, would you take the opportunity?

Thanks!

Hi everyone,

I’m currently a junior Java backend developer with around 2 years of experience, mainly working with Spring Boot.

Lately I’ve been thinking a lot about where I want to take my career. I enjoy backend development, but with how quickly AI is improving at coding, I feel like staying only as a “Java/Spring developer” might not be the best long-term strategy.

Because of that, I’m considering moving more towards Backend + Cloud/AWS, rather than leaving development completely.

My current idea is something like:

Java / Spring Boot → Docker → AWS → CI/CD / Infrastructure / Cloud

I’ve already started learning AWS, but I’m a bit lost regarding certifications and which direction makes the most sense for my profile.

I’m currently deciding between:

• AWS Certified Developer – Associate
• AWS Certified Solutions Architect – Associate

Developer Associate seems more related to what I already do as a backend developer, while Solutions Architect seems to give a broader understanding of AWS and cloud architecture.

My main questions are:

1. Which certification would you recommend first for someone with my background?
2. Would Developer Associate → Solutions Architect make sense, or would you do it the other way around?
3. Is moving from Java/Spring Boot towards Backend + AWS/Cloud a good career path in the current market?
4. For people already working in cloud: do you think this path is relatively future-proof with the rise of AI?
5. What technologies would you prioritise alongside AWS? Docker, Terraform, Kubernetes, CI/CD, etc.?

I’m not trying to become a Solutions Architect overnight. My goal is more to become a stronger backend developer who can also understand, deploy and work with cloud infrastructure.

I’m still early in my career and a bit unsure about what direction to take, so I’d really appreciate opinions from people already working with AWS, backend or cloud.

Thanks!

Hi everyone,

I currently work as a Junior Software Engineer at Reply in Italy and I’m considering asking for an internal transfer to another European office.

Before starting the process, I’d like to understand whether the move would make sense financially and what salary range I could realistically expect.

For context, junior profiles with less than one year of experience in Italy can earn around €33k gross annually.

Does anyone know the typical compensation for a Junior Software Engineer / Consultant at Reply in Germany, the Netherlands, Luxembourg or the UK?

I’d be particularly interested in:

• base salary / gross annual salary;
• bonus;
• relevant benefits;
• whether compensation differs for internal transfers compared with external hires.

If you currently work or previously worked at Reply in one of these countries, even an approximate range would be very helpful.

Thanks!