Analytics Engineer
Lovable, Stockholm
What you will do
- Build and maintain modular, tested, and version-controlled data models that agents can reliably discover, interpret, and query
- Partner with domain teams to translate business logic into reusable models and metrics with explicit definitions and clear context
- Own the semantic layer, defining consistent metrics and data contracts across domains so agents answer business questions accurately
- Collaborate with Data Platform Engineers to optimize query performance and warehouse cost for agent-driven analytics
- Automate documentation, lineage, and governance so agents can understand data meaning, provenance, and usage constraints
- Establish standards for analytics development, data modeling, and naming conventions that make agent-mediated self-service analytics reliable for everyone
What you need
- Expertise with SQL, dbt, SQLMesh or similar tools (data modeling, testing, macros, docs)
- Experience with data warehousing concepts, cloud warehouses (Snowflake, BigQuery, Redshift, Databricks) and BI tools (Looker, Tableau, Power BI, Hex, Metabase, etc)