Data Analytics Engineer
Core
Design, maintain, and govern the data transformation layer and semantic layer to enable trustworthy data products for business decision-making and AI agents.
Role type
Senior Data Analytics Engineer (AI-enabled)
Builds
Production data models, data warehouse transformations, and semantic layer documentation for internal stakeholders and AI agents.
Domain
Technology / Data Engineering / Cloud Data Warehousing
Deliverable
production ML models | product features
Required skills
Expert SQL, Python, LLMs and agentic coding tools, cloud data warehousing (BigQuery/Snowflake), modern transformation frameworks (dbt/Dataform/SQLMesh), Git, orchestration tools (Airflow/Dagster/Prefect), data modeling, data governance, requirements gathering.
Preferred skills
Experience in Analytics Engineer, Data Engineer, or Data Analyst roles, architectural thinking, independent judgment.
Technologies
BigQuery, Snowflake, Dataform, dbt, SQLMesh, Airflow, Cloud Composer, Dagster, Prefect, Git, Claude Code, Cursor
Responsibilities
Design, write, review, and ship SQL models transforming raw data into usable data products. Own and maintain the data transformation layer and data dictionary. Proactively monitor the data warehouse to identify opportunities for improvement. Turn ambiguous business asks into modeled data with clear business rules. Implement measures to improve data quality, accuracy, lineage, and access. Diagnose and resolve data incidents. Review teammate code to maintain production environment hygiene. Collaborate with Business Analysts, Data Engineers, and Data Scientists to empower data-driven decisions.
Seniority
Senior, hands-on IC