Data Engineer

Legora Legora · Vertical AI · Stockholm, Sweden · Engineering & Product

Legora is seeking a Senior Data Engineer to own their data platform end-to-end, focusing on infrastructure, pipelines, and enabling analysts and product teams. The role involves shaping architecture, setting standards, and building a programmable, observable data platform. Responsibilities include owning the data platform, building ingestion pipelines, driving reverse ETL, leading warehouse design, raising DevEx through CI/CD, embedding quality and security, and designing for programmability by automated systems.

What you'd actually do

  1. Own the data platform: develop and maintain core data infrastructure across the warehouse, data lake, orchestration, observability, and governance layers.
  2. 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.
  3. Drive reverse ETL: push clean, modeled data back into operational tools to power workflows and automations across the business.
  4. Lead warehouse design: collaborate with analytics engineers to define modeling conventions, enforce schema governance, and keep our dbt project clean, tested, and scalable.
  5. 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.

Skills

Required

  • Data engineering or data platform role experience
  • Modern cloud data platform experience (Snowflake, BigQuery, Redshift, Databricks)
  • dbt experience
  • Understanding of distributed systems
  • Pipeline orchestration experience
  • Infrastructure as code experience
  • Experience improving DevEx and CI/CD
  • Experience across full data flow (ingestion, ETL, modeling, self-service)
  • Clear technical communication
  • Documentation skills

What the JD emphasized

  • own our data platform end-to-end
  • shape the architecture
  • set the standards
  • fully operable by automated systems
  • programmable surface
  • not just a collection of pipelines someone has to babysit
  • the right data is in the right place, reliably
  • everyone who needs it can use it without filing a ticket
  • Own the data platform
  • Raise the DevEx bar
  • Embed quality and security
  • Design for programmability
  • operate, queried, and orchestrated by automated systems
  • Own problems fully
  • Thrives where the answers aren't always clear and processes are few