Senior Data Platform Engineer

Source Meio β€” Netherlands Β· Posted ~20 hours ago

Senior Remote EUR 100000-115000 per year plus 0.5-0.75% equity

Skills

Data engineering Data platform development Data integration Data cleaning and transformation Data quality and reliability AI data infrastructure Financial and operational data integration Enterprise data systems Python PostgreSQL AI GraphRAG Data platforms ERP systems Accounting systems Billing systems

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Summary ✨ AI‑Generated

An early-stage AI company is seeking a senior data platform engineer to build reliable foundations for intelligent applications in the financial sector. You will integrate data from accounting, enterprise resource planning, billing, and spreadsheet systems, improve data quality, and connect disparate information sources so AI agents can make better-informed decisions. The role is remote-first and offers EUR 100,000–115,000 annually plus equity.

Highlights

Competitive annual compensation of EUR 100,000–115,000 plus 0.5–0.75% equity in an early-stage AI venture. Work remotely in a senior engineering role building foundational data infrastructure, integrating complex business systems, and improving the reliability of data used by advanced AI applications.

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. πŸ˜‚ 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 πŸ˜… 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 like 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.