Staff Analytics Engineer

The work

Own the analytics engineering layer: dimensional models, tested metrics, and orchestration that scientists and eval engineers trust. You will document grain, enforce tests, and keep warehouse costs predictable — without naming clients in public materials.

You will

• Model curated marts in dbt with documented grain, surrogate keys, and freshness SLAs
• Implement data quality checks (uniqueness, referential integrity, anomaly thresholds) that fail CI
• Partner with data scientists on feature tables and with eval teams on golden dataset extracts
• Review query patterns and materialisation choices to control warehouse spend

You likely have

• 7+ years in analytics engineering or data platform roles with dbt in production
• Deep SQL and dimensional modelling; experience with Snowflake or BigQuery at scale
• Orchestration familiarity (Airflow, Dagster, or equivalent) and incident runbooks
• Privacy discipline — no raw PII in dev schemas that leave secure environments