Astrana Health is seeking a highly motivated Manager - Data Engineering to join their growing team. This role will lead a team of data engineers, collaborating with various stakeholders to design and implement robust data pipelines and solutions that enhance patient outcomes and drive innovation in healthcare data management.
Responsibilities:
- Lead and mentor a team of data engineers, fostering a culture of continuous learning, innovation, and operational excellence
- Partner with cross-functional teams to design and implement scalable data pipelines and models aligned with business needs and industry best practices
- Oversee the development, deployment, and maintenance of enterprise-grade ELT processes, data marts, and business intelligence assets
- Own and evolve data quality frameworks, ensuring proactive monitoring, troubleshooting, and resolution of data issues
- Champion the adoption of automation and modern data engineering practices, driving efficiencies in pipeline management and data delivery
- Guide your team in building domain knowledge around healthcare operations, ensuring data solutions comply with regulatory and security requirements
- Contribute to strategic planning for the data engineering function, including resource allocation, technology selection, and process improvement initiatives
- Support and enforce software development best practices, including code reviews, source control, CI/CD, and testing
Requirements:
- Bachelor's degree required in computer science, engineering, healthcare, analytics, or a related field; Master's degree preferred
- 5+ years of experience in data engineering or software development roles, with at least 2+ years in a leadership or management capacity
- 2+ years of experience with medical claims in healthcare and/or managed care
- Strong expertise in building scalable ELT/ETL pipelines using modern data platforms and cloud-based services (e.g., AWS, Azure)
- Advanced proficiency with SQL and scripting/programming languages such as Python or Spark
- Solid understanding of database structures, data modeling (normalized, star schema, snowflake), and data warehousing concepts
- Deep understanding of professional software engineering practices including SDLC, version control, CI/CD, and automated testing
- Strong communication and stakeholder management skills, with the ability to translate technical concepts for non-technical audiences
- Experience working with Databricks or similar distributed computing platforms
- Familiarity with BI tools such Power BI