Senior Data Engineer

SOURCE.ME; Amsterdam; Remote; EUR 95,000 - 115,000; Full time

Benefits offered by this job

Equity

Remote-first

Weekly Amsterdam meetups

Job summary

SOURCE.ME is building an early-stage AI platform for the finance sector. We’re hiring a Senior Data Platform Engineer to lay the foundations for AI, focusing on data extraction, cleaning, and connecting disparate systems to a reliable product data layer.

Ideal candidates have 6–10+ years building backend/data platforms or ML infra, with strong coding and data modelling skills. GraphRAG and knowledge graphs are a plus; Amsterdam weekly meetups are possible in a remote-first setup.

Qualifications

• 6–10+ years building backend systems, data platforms or ML infra.
• Strong coding skills and data modelling knowledge.
• Experience with AI-powered products and graph knowledge graphs beneficial.

Responsibilities

• Build the foundations underneath AI, ensuring reliable data for product use.
• Ingest and clean data from diverse systems; connect data sources.
• Develop data platforms with graphs/knowledge graphs and GraphRAG approaches.
• Collaborate with senior leadership to guide architectural decisions.

Job description

Senior Data Platform Engineer | AI, GraphRAG & a Bit of Everything Else

€100–115k + 0.5–0.75% equity | Remote-first | Amsterdam

Working with a small, early-stage AI company that's building something pretty ambitious for the finance world. Not another dashboard, not another chatbot with an LLM bolted onto it.

Sounds fancy, but the problem they're solving is fairly straightforward to understand.

Businesses have financial and operational data all over the place. Accounting systems, ERPs, billing platforms, spreadsheets, you name it. None of it particularly enjoys talking to the other bits.

Now imagine trying to get AI agents to make sensible decisions using all of that.

That's where you come in.

They're looking for a Senior Data Platform Engineer to build the foundations underneath the AI.

Getting data out of different systems, cleaning it up, connecting the dots and making sure it's actually reliable enough for the product to use.

Because an AI confidently giving a CFO the wrong answer isn't exactly ideal.

The Engineering Bit

There's a fair amount to get stuck into here.

• Python, SQL, PostgreSQL, data modelling, ETL/ELT, ingestion pipelines and external API integrations.
• Cloud experience is important, ideally GCP, alongside the usual production engineering fundamentals: Terraform, CI/CD, testing, monitoring.

Then there's the even more interesting AI side.

Knowledge graphs, entity relationships, GraphRAG, embeddings and retrieval. They're building around SurrealDB, which combines graph and vector capabilities.

You don't need to have used SurrealDB before. Experience with Neo4j or similar graph technologies would be interesting.

What matters is understanding how to build data systems that AI products can genuinely depend on.

Not just getting a demo working. Getting the actual thing working.

Who I'm Looking For

Someone who's been around the block a bit

Ideally 6–10+ years building backend systems, data platforms or ML infrastructure.

You can write good code, understand how data should be modelled, know your way around production pipelines and aren't frightened of making architectural decisions.

I'd particularly like to speak with engineers who've worked on AI-powered products and understand the difference between data being available and data being trustworthy.

Experience with GraphRAG or knowledge graphs would really get my attention.

And you'll need to be comfortable getting your hands dirty. This isn't a position where you draw a few diagrams, hand them over to somebody else and disappear into meetings.

Why Bother?

Well, for starters, you're getting in early. You'll work directly with the incoming CTO and have a genuine say in how the platform is built, right-hand if you like, potential to step into a team lead role.

Not pretending to have ownership while somebody three levels above you makes all the decisions.

There's a small engineering team already in place, with a good mix of people and backgrounds.

As things grow, there's the potential to build out the data engineering function and take on more technical leadership, if that's something you want.

It's remote-first, although they'd ideally want everyone to get together in Amsterdam once a week.

And the package is decent.

€95k–115k base, plus 0.5–0.75% equity. The equity is a particularly interesting part of this, given how early you'd be joining. Normally cliff vesting stuff.

Interested?

I appreciate this is a slightly unusual combination of skills.

Strong data engineering, proper software engineering, a bit of AI and ideally some experience with knowledge graphs or GraphRAG.

But that's also what makes it a good opportunity.