• Design, build, and maintain scalable ETL/ELT pipelines using AWS, Airflow, and other technologies to ingest and transform healthcare and TPA data, including claims, provider, and eligibility sources. • Develop and operate resilient data architectures and workflows (Airflow, CloudWatch, ECS, DAGs) with strong CI/CD, observability, and governance. • Build data applications and processes using Python, SQL, and Django; manage and query data in PostgreSQL, Oracle, and cloud-native databases. • Examine, extract, cleanse, and load data while implementing quality assurance rules and tools to ensure consistent and accurate data. • Work with healthcare-specific data processes such as EDI file transfers, claims adjudication, audits, eligibility verification, and reporting workflows. • Collaborate with cross-functional teams (Data Analysts, Data Scientists, Product, Reporting, Account Management) to define requirements and deliver data-driven solutions. • Ensure data quality, integrity, and security through automated validation, auditing, and monitoring, with compliance to HIPAA and CMS regulations. • Monitor, maintain, and tune pipeline performance; proactively troubleshoot and resolve complex data flow and system issues. • Provide technical mentorship to Data Engineers, sharing expertise in data modeling, pipeline development, and troubleshooting practices. • Research and propose improvements to the tech stack and data engineering processes. • Participate in sprint planning, refinement, and estimation to support implementation awareness and delivery.