- Write and optimize SQL to extract, join, and aggregate data across large relational datasets.
- Use Python to clean, transform, and analyze data that doesn't fit neatly into a query.
- Independently explore datasets to surface trends, anomalies, and opportunities.
- Build and maintain dashboards and recurring reports that stakeholders rely on.
- Partner with product and customer success teams to scope ambiguous questions into answerable analyses.
- Investigate data quality issues and collaborate with engineering to resolve them.
- Document data definitions, metrics, and methodology for reproducibility.
- Present findings and recommendations to both technical and non-technical audiences.
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