We're seeking a Staff Data Engineer to join one of the fastest-growing AI legal tech companies in Europe. You'll take technical ownership of the data platform behind how we run the business: the pipelines, the warehouse, and the definitions behind the numbers our leadership team actually uses.You'll report to our Head of Engineering and work alongside a colleague who owns the business-facing side of data, plus our infrastructure and application engineers. This is a senior individual contributor role with no line management in either direction, roughly 70% hands-on building, 30% defining, documenting and explaining.Your Challenge and Opportunity in This RoleJUPUS supports hundreds of law firms across Europe, and our customer base is growing roughly 4x a year. Our data platform has grown with it (ClickHouse, dbt, Python extract-load pipelines into an S3 data lake, orchestration in GitHub Actions) and it has grown fast.Your job is to make it trustworthy. That means modernising what already exists, making historical trends a record of what actually happened rather than a nightly re-derivation of it, and owning the definitions behind the metrics that reach our board. This is not a greenfield build, and it is not a maintenance seat. It is a real platform with real problems, and you would own it.TasksOwn the data platform end to end: ingestion and the raw layer, the ClickHouse warehouse, and the dbt project on top of it. You're the person who can say whether a number is wrong or the pipeline is.Make our numbers trustworthy: reliability, correctness, and a history that holds up, so that a trend is a record of what actually happened rather than a re-derivation of it.Own the metrics the company runs on, starting with our customer health score- the definition, the denominator, the eligibility rules and the known limitations, not just the SQL underneath them.Turn business questions into durable metrics: work directly with Customer Success, Sales, Product and leadership to under