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Sr. Analytics Engineer
Skills
Agility TrainingData AnalyticsData ArchitectureDatabasesDriftModelingOptimization
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 4+ years of professional experience in analytics engineering data engineering or highly technical data analytics roles
- Expert-level SQL proficiency and deep data modeling experience
- 2+ years of hands-on experience building deploying and maintaining modular data pipelines using dbt in production
- Experience designing schemas and optimizing query performance on modern cloud data platforms such as Snowflake Redshift or BigQuery
- Comfort with production git workflows and automated data quality testing practices
- Experience partnering with analytics operations or business teams and translating complex data structures into clear documentation
Nice to have
- HIPAA-compliant data experience
- EHR experience
- Digital health experience
- Snowflake familiarity
- AI-assisted development tools
- Fivetran experience
- Data quality mindset
- Python proficiency
Day to day
- Design, build, and optimize modular dbt pipelines and technical schemas for a modern analytics ecosystem.
- Translate ambiguous business and product requirements into trusted production-grade data models across Analytics Operations and Data Engineering.
- Diagnose performance bottlenecks and reduce query latency and warehouse costs while supporting a strategic migration to Snowflake.
- Strengthen engineering quality through rigorous peer reviews refactoring technical debt enforcing data security and mentoring junior teammates.