Data Engineer

About the role

Lexroom http://lexroom.ai/ is building the AI platform where legal work gets done. In just over two years, we've grown from zero to €25M ARR, and today more than 20,000 legal professionals across Italy, Spain, Germany, France, and Bulgaria rely on Lexroom http://lexroom.ai/.

We're backed by $73M from Left Lane Capital, Base10 Partners, and Eurazeo, and we're a team of around 300 builders who move fast, say things straight, and own each outcome.

Our next goal? Become Europe's most-used legal product.

WHY LEXROOM http://lexroom.ai/?

- Shape the Standard: Be part of the team setting the benchmark for legal AI in Europe.

- Work with the Best: Collaborate with exceptional colleagues in a culture that values competence, curiosity, and ambition.

- Deliver Meaningful Results: Your contribution will directly influence how legal professionals work—faster, clearer, and more efficiently.

At Lexroom http://lexroom.ai/, we leave buzzwords behind. Here, you’ll build something that lasts: a trusted platform, a strong reputation, a new standard for the legal world.

The Role

Our proprietary legal data is the engine behind everything Lexroom does. As we scale our Data team, we’re looking for a Data Engineer to own and improve the pipelines and infrastructure behind our legal knowledge base and document processing. You’ll report to our Head of Data and work closely with Product, AI Engineering, and Legal Engineering.

Your key responsibilities

- Legal Data Infrastructure: Manage and improve the infrastructure behind our legal database: case law, regulations, legal documents, and the links between sources.

- Document Processing Pipelines: Build and improve the pipelines that process our users’ document libraries, from OCR and text extraction to context extraction, metadata tagging, and anonymization.

- Data Security & Privacy: Make sure files uploaded to private user libraries are handled securely and in line with privacy standards.

- Reliability & Monitoring: Own pipeline health end to end, with monitoring, alerting, and data quality checks that catch issues before users do.

- Scale & Performance: Optimize pipelines for large data volumes and propose architectural changes that make them faster and more robust.

What we’re looking for

- Experience: 4+ years of hands-on experience in Data Engineering, ideally in fast-growing tech, SaaS, or AI companies.

- Python & Data Pipelines: Strong Python skills and proven experience designing and running scalable ETL pipelines.

- Databases & Storage: Hands-on experience with SQL and NoSQL databases, object storage, and vector databases.

- Cloud Infrastructure: Hands-on experience with cloud data infrastructure. GCP is preferred; AWS or Azure also work.

- Monitoring & Ownership: Experience setting up monitoring and alerting for production pipelines, and the autonomy to own them end to end.