Senior Data Platform Engineer Berlin, Germany
Role details
Job location
Tech stack
Job description
We build the learning platform behind education programmes reaching children across Kenya and Nigeria. Every lesson a child takes generates a signal. Our data platform turns that signal into the evidence that tells us, our funders and the governments we report to, whether children are actually learning to read. So when a number is wrong, a decision about a child's education is wrong. Getting that right, at scale, on a platform you can trust, is the job., * Own the data platform end-to-end: Ingestion, warehouse, transformation tooling, BI, scheduling, observability, governance. Today that's Kafka Redshift, dbt Core, GitHub Actions, and Metabase. Where it goes next is yours to argue for.
- Build the governed layer that makes AI-assisted analytics trustworthy: Semantic and metric definitions, data contracts, tests. Make sure that numbers that reach a funder or a government programme are reproducible and audited.
- Put AI to work on the platform itself: Freshness, cost and anomaly detection, pipeline triage, automated first-pass resolution. Automate repeatable and verifiable tasks.
- Build observability, governance and access control across the stack: scoped credentials, RBAC and access tiers in the warehouse and Metabase, audit, lineage, compliance.
- Partner with product engineering on product event data: Making it first-class without breaking the warehouse, establish data contracts at that boundary. Collaborate on infrastructure to fuel in-app analytics products.
This is right for you if
- You have opinions about where AI belongs in a data platform and where it categorically doesn't and you can defend the line.
- You can dissect dbt's tradeoffs and say when the answer is a semantic layer (MetricFlow, Cube, Malloy), SQLMesh, or something we haven't tried yet
- You have broad command of the modern data stack. Stream and batch, OLAP, orchestration, transformation, observability. You care about the tradeoffs between them.
- You're fluent enough in AWS, IaC, and CI/CD to ship and run your own tooling without waiting on anyone. (Our platform team owns the underlying infrastructure - k8s, SSO, networking - so it won't be your day-to-day job.)
- You're comfortable being a team of one. You'll be the only data engineer on a four-person data team, owning the platform end to end.
This probably isn't for you if
- dbt and the warehouse are the edges of your world.
- You want a big data team, peers to pair with, or a clearly bounded specialist lane. This is a generalist role where you will be collaborating with other roles.
- You want a finished platform to optimise rather than one to rebuild and have opinions about.
Our Stack
- An event-sourced microservice backend, with Kafka as the source of truth.
- Events are sunk and flattened into Redshift.
- dbt Core transforms raw events into datasets, scheduled through GitHub Actions.
- Data is exposed through Metabase (open source).
What we offer:
- Work on one of the biggest problems in the world: ensuring every child gets the education they deserve.
- A small, high-impact team where your work shapes our direction.
- Annual up-skilling budget
- Competitive equity-awarding model
- High degree of flexibility with regard to working hours and vacations
- A hybrid working arrangement, based in Berlin
- Compensation between €70,000 and €87,500 (if leveled as Senior)
Requirements
Do you have experience in Redshift?