- Mentor and support data analysts, data engineers and developers, fostering a collaborative and psychologically safe environment.
- Set high standards for technical excellence in SQL, dbt modeling, and LookML architecture.
- Collaborate on the migration of legacy logic from Redshift/Postgres into performant Databricks silver and gold layers.
- Independently implement complex data models in dbt, demonstrating expertise in modularity, testing, and performance optimization on Spark.
- Own the LookML layer, ensuring explores and dashboards are performant, intuitive, and accurate.
- Act as a "Hybrid Analyst," balancing long-term engineering projects with ad-hoc requests to support the business.
- Translate stakeholder questions into Looker-based reports and visualizations.
- Lead technical data planning through discovery, design, and release, ensuring clear documentation for data catalogs and version tracking.
- Identify opportunities for "data debt" reduction and architectural improvements in the Lakehouse and semantic layers.
- Proactively address system characteristics like latency and throughput, ensuring data pipelines are optimized for cost and speed.
- Act as a subject matter expert in your data domain, contributing to business strategy.
- Provide engineering perspectives on the product roadmap, clearly communicating data feasibility and reporting limitations.
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