Requirements
- Experience: 5-10 years of experience in data engineering
- Strong exp in Snowflake DWH and its components
- SQL — advanced (CTEs, window fns, tuning)
- Amazon QuickSight (BI visualizations)
- Python (pipelines, data processing)
- Data integrity & root cause analysis
- ETL / ELT pipeline development
- dbt (data build tool)
- AWS Glue / Lambda / S3
- Rockset (analytical engine)
- SQL-heavy role
- Snowflake critically important
- Amazon QuickSight used to render visualizations for clinical stakeholders
Nice to Have
- Data Architecture: Experience designing or optimizing data lake solutions
- Security Practices: Understanding of data security practices, data governance, and compliance for secure data processing
- Automation & CI/CD: Familiarity with CI/CD tools to support automation of deployment and testing
- Big Data Technologies: Knowledge of big data processing tools like Spark, Hive, or related AWS services
- Advanced Analytics: Background in analytics or data science to contribute to more data-driven decision-making
- Cross-Functional Collaboration: Experience collaborating with non-technical teams on business goals and technical solutions
