AWS Senior Data Engineer - Remote

Job Type: Remote Work Timings: Flexible with US overlap preferred InCommon is hiring on behalf of a stealth-mode startup focused on building transformative AI-powered solutions. A US-based healthcare analytics SaaS company delivering cost transparency and advanced analytics to health plans, self-funded employers, and benefits consultants. They process complex medical, pharmacy, and eligibility datasets under HIPAA and SOC2 compliance to power actionable client insights. This is a senior, high-autonomy data engineering role owning the data platform end-to-end. The near-term priority is migrating a substantial legacy SQL Server stored procedure codebase into a modern, maintainable, and testable pipeline architecture.The work spans AWS-hosted SQL Server, AWS infrastructure, and Airflow-based ETL pipelines, supporting both internal operations and client-facing data onboarding. You will audit and refactor legacy T-SQL logic, design and maintain ETL/ELT pipelines for claims, eligibility, pharmacy, and premium datasets, and own SQL Server administration including query tuning, HA/DR, and schema management. Build data validation, anomaly detection, and reconciliation checks across critical pipelines Maintain technical documentation data dictionaries, lineage diagrams, runbooks as a standard habit5+ years in data engineering or senior DBA roles in production environmentsExpert-level T-SQL: complex queries, window functions, CTEs, performance tuning, execution plan analysisDemonstrated experience refactoring legacy stored procedure logic into modern pipeline architectures (dbt, Python, Airflow)Proficiency in Python for ETL, pipeline components, and data validationProduction experience with Apache Airflow and dbtWorking knowledge of AWS (S3, RDS, or equivalent) and SQL Server on AWSPractical experience with SOC2 and HIPAA requirements in a real production context Job Type: Remote Work Timings: Flexible with US overlap preferred InCommon is hiring on behalf of a stealth-mode startup focused on building transformative AI-powered solutions. A US-based healthcare analytics SaaS company delivering cost transparency and advanced analytics to health plans, self-funded employers, and benefits consultants. They process complex medical, pharmacy, and eligibility datasets under HIPAA and SOC2 compliance to power actionable client insights. This is a senior, high-autonomy data engineering role owning the data platform end-to-end. The near-term priority is migrating a substantial legacy SQL Server stored procedure codebase into a modern, maintainable, and testable pipeline architecture.The work spans AWS-hosted SQL Server, AWS infrastructure, and Airflow-based ETL pipelines, supporting both internal operations and client-facing data onboarding. You will audit and refactor legacy T-SQL logic, design and maintain ETL/ELT pipelines for claims, eligibility, pharmacy, and premium datasets, and own SQL Server administration including query tuning, HA/DR, and schema management. Build data validation, anomaly detection, and reconciliation checks across critical pipelines Maintain technical documentation data dictionaries, lineage diagrams, runbooks as a standard habit5+ years in data engineering or senior DBA roles in production environmentsExpert-level T-SQL: complex queries, window functions, CTEs, performance tuning, execution plan analysisDemonstrated experience refactoring legacy stored procedure logic into modern pipeline architectures (dbt, Python, Airflow)Proficiency in Python for ETL, pipeline components, and data validationProduction experience with Apache Airflow and dbtWorking knowledge of AWS (S3, RDS, or equivalent) and SQL Server on AWSPractical experience with SOC2 and HIPAA requirements in a real production context