Data Engineer
Introduction: As a Data Engineer, you will be responsible for working with healthcare or payer domain data, specifically with member, claims, provider, quality, or reference data. You will be utilizing your expertise in Snowflake, DBT, and SQL to develop complex transformations, optimize performance, and build curated data layers using medallion architecture principles.
Responsibilities:
- Snowflake SQL: Develop complex transformations, optimize performance, and work confidently with CTEs, advanced joins, and analytic/window functions.
- Snowflake Data Engineering: Build curated data layers using medallion architecture principles across bronze, silver, and gold datasets.
- Semantic Modeling / Semantic Layer Engineering: Define business-friendly metrics, dimensions, relationships, and reusable semantic views on top of Snowflake data.
- Snowflake Cortex / AI-Enabled Analytics: Experience supporting Snowflake Cortex-based analytics workflows, semantic intelligence, or agentic analytics use cases.
- Data Quality, Profiling, and Validation: Identify natural and surrogate keys, assess cardinality and distribution, validate transformations, and ensure trustworthy semantic outputs.
- Communication and Collaboration: Work across engineering, product, and analytics teams, clarify requirements, and proactively drive work with limited direction.
Requirements:
Required Skills: Snowflake, DBT, SQL, Health Care, Modeling, Data Quality, Dimensional Modeling, Collaboration, Communication, Data Engineering.
Preferred Skills: Reference Data, Semantics, Use Cases, Analytical Skill, Analytics, Artificial Intelligence, Workflow.
