Data Engineer
Core
Design, build, and maintain scalable data pipelines and warehouse models to transform life science and healthcare data into clean, trusted datasets for analytics and decision-making.
Role type
Data Engineer
Builds
Scalable data pipelines, data warehouse structures (dimension/fact tables), and data marts
Domain
Life Science / Healthcare / Data Engineering
Deliverable
production ML models
Required skills
Advanced SQL, Data warehouse development (dimensional modeling, SCDs), ETL/ELT tools (dbt, Python, SSIS), Git version control, Cloud platforms (Azure, AWS), Snowflake
Preferred skills
Snowflake, dbt certification, dbt model testing and documentation
Technologies
dbt, Python, SQL, Snowflake, Azure, AWS, SSIS, PowerCenter, Git
Responsibilities
Develop scalable data pipelines, design and maintain data orchestration processes, build complex dbt models, implement slowly changing dimensions, manage data mart updates, build conformed dimensions via MDM integration, collaborate with analysts and scientists on data requirements
Seniority
Mid-level, hands-on IC
