Senior Data Engineer

About the company InCommon is hiring on behalf of a US-based healthcare analytics SaaS company that delivers cost transparency and advanced analytics to health plans, self-funded employers, and benefits consultants. They process complex medical, pharmacy, and eligibility datasets to power actionable insights — and operate under HIPAA and SOC2. The team is lean and technically strong. Engineers own their domain end-to-end. About the role This is a senior, high-autonomy role owning the data platform. You won't be working off tickets — you'll set the technical direction, identify problems before they escalate, and drive modernization independently. You receive an objective, not a step-by-step plan. The near-term priority is migrating a substantial legacy SQL Server stored procedure codebase into a modern, maintainable, testable data pipeline architecture. You'll assess the existing procedures, design the target state, and execute with minimal supervision.

The work spans AWS-hosted SQL Server, AWS infrastructure, and Airflow-based ETL pipelines — supporting both internal operations and client-facing data onboarding. What you'll do Audit, document, and refactor legacy T-SQL stored procedures into modular dbt models, Python transformations, or Airflow DAGs — preserving business logic fidelity through validation frameworks Design and maintain ETL/ELT pipelines for ingesting claims, eligibility, pharmacy, and premium datasets from diverse client sources Own SQL Server administration on AWS: query tuning, index management, schema changes, backups, HA/DR Build data validation, anomaly detection, and reconciliation checks across critical pipelines Enforce SOC2 and HIPAA-compliant access controls, encryption, and audit logging Maintain technical documentation — data dictionaries, lineage diagrams, runbooks — as a habit, not on request What we're looking for 5+ years in data engineering or senior DBA roles in production environments Expert-level T-SQL: complex queries, window functions, CTEs, performance tuning, execution plan analysis Demonstrated experience refactoring legacy stored procedure logic into modern pipeline architectures Proficiency in Python for ETL, pipeline components, and data validation Production experience with Apache Airflow and dbt Working knowledge of AWS (S3, RDS, or equivalent) and SQL Server on AWS Practical experience with SOC2 and HIPAA requirements — not just theoretical Strong async working style; comfortable operating without daily check-ins Even better if you have SSIS experience (relevant to the legacy migration context) Background working with healthcare data (claims, eligibility, pharmacy)