Data Engineer

ABOUT US Legora is redefining how legal work gets done. Not built for lawyers, built with them. We work alongside the world’s best legal teams, who expect excellence, precision, and speed, and we hold ourselves to the same bar. Our AI-native workspace lets legal professionals move faster, think more clearly, and operate with sharper precision. By analysing thousands of documents in minutes and powering end-to-end workflows, we cut through complexity, teams can focus on what matters: judgment, strategy, and outcomes. 1,000+ customers across 50+ countries trust us, including Cleary Gottlieb, Goodwin, Linklaters, White & Case, Dentons, and Barclays. We’ve scaled to $100M+ in ARR, with teams across Europe, North America and APAC, and continue to expand through acquisitions including Qura, Walter AI and Graceview. We partner with world-class performers: including Aaron Judge and the New York Yankees, Ludvig Åberg (and his caddie), and campaigns featuring Jude Law. Joining Legora means three things. - We lean in: ownership over titles, outcomes over intentions. - We fight for excellence: high standards, direct, ego-free feedback. - We grow together: as a team and with our customers. Mission before ego. Everyone contributes. No one coasts. If you’re driven by impact, pace, and raising the bar. This is the place. THE ROLE Legora is growing fast, and data is at the center of how we build, scale, and win. We're looking for a Data Engineer to own our data platform end-to-end, from the infrastructure that powers it to the pipelines that feed it, and the foundations that make every analyst and product team faster. This isn't a role where you maintain someone else's decisions. You'll shape the architecture, set the standards, and build a data platform designed to be fully operable by automated systems, where the stack itself is a well-structured, observable, and programmable surface, not just a collection of pipelines someone has to babysit. You'll work closely with our analytics engineers, product teams, and RevOps to make sure the right data is in the right place, reliably, and that everyone who needs it can use it without filing a ticket. WHAT YOU'LL BE DOING - Own the data platform: develop and maintain core data infrastructure across the warehouse, data lake, orchestration, observability, and governance layers. - Build and maintain data ingestion: design robust ELT pipelines using dlt and implement declarative configuration for ingestion and transformation, partnering with domain teams to scale coverage. - Drive reverse ETL: push clean, modeled data back into operational tools to power workflows and automations across the business. - Lead warehouse design: collaborate with analytics engineers to define modeling conventions, enforce schema governance, and keep our dbt project clean, tested, and scalable. - Raise the DevEx bar: implement CI/CD pipelines for data systems, define platform best practices, and support self-service enablement so the data team can ship fast and safely. - Embed quality and security: ensure data quality, lineage, and security standards are built into workflows from the start, not bolted on after. - Design for programmability: architect the stack so it can be operated, queried, and orchestrated by automated systems, clean interfaces, structured outputs, and well-documented contracts throughout. WHO YOU ARE - Solid experience in a data engineering or data platform role, depth and ownership matter more to us than industry background. - Strong hands-on experience with a modern cloud data platform (Snowflake, BigQuery, Redshift, Databricks, or similar), dbt, and a solid grasp of distributed systems and how data moves at scale. - Comfortable with pipeline orchestration and managing infrastructure as code, you have opinions on how to do both well. - You've raised the bar on DevEx and CI/CD somewhere before: better testing, cleaner deployments, less fire-fighting. - Can work across the full data flow, from ingestion and