SQL Analytics Engineer Expert

What You'll Do5

• Build realistic analytics scenarios that carry a case from raw tables through to tested data models, keeping each one close to how a working engineer would tackle it.
• Write reference answers that lay out the modeling choice and the query logic behind every step.
• Score model output on SQL correctness and on how the query behaves in the warehouse.
• Flag submissions that read clean but return wrong rows or burn needless compute.
• Document your modeling rationale in clear written English so other reviewers can follow each decision.

Requirements8

• Two or more years in analytics engineering, or analytics work built around heavy SQL.
• Expert command of joins, window functions, CTEs and query optimization.
• Hands on use of a modern warehouse such as BigQuery, Snowflake or Redshift.
• Written English strong enough to explain why a model or query took the shape it did.
• Availability for at least 10 hours each week.
• Preferred: dbt or another transformation framework.
• Preferred: dimensional or semantic data modeling experience.
• Preferred: orchestration exposure through Airflow, Dagster or similar.

Who Should Apply

Analytics engineers with 2+ years of SQL-heavy work who want a hand in how AI models reason about data. You should move with ease inside BigQuery, Snowflake or Redshift, and you can put a modeling decision into plain writing that another engineer follows without asking questions.

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