Data Engineering Manager

Architect and implement secure, efficient ETL workflows using SQL, Python, and AWS services to support healthcare analytics. Lead the design, development, and maintenance of scalable data pipelines and cloud-based infrastructure for ingesting and transforming large-scale healthcare claims datasets, with a focus on ambulatory and outpatient services. Oversee data quality, governance, and reliability across all HSG data products, ensuring accuracy in data structure and content used to derive analytical insights at the facility, provider, payer, and procedure level. Utilize claims data to identify outpatient utilization trends, referral patterns, and network leakage, translating complex datasets into strategic insights for hospitals and health systems. Collaborate with clinical, operational, and executive stakeholders to support service line planning, network integrity analysis, and performance improvement initiatives. Manage the integration of AI-driven tools into data engineering workflows to automate processes and enhance predictive modeling. Direct the development of HSG's internal data platform and architecture, and lead efforts to modernize legacy pipelines, including implementing improved data models to optimize query performance and scalability. Establish best practices for DevOps and CI/CD pipelines, including version control standards using GitHub. Mentor junior engineers and contribute to the development of standardized cloud architecture templates and QA processes.

100% telecommuting permitted. Candidate may reside/work anywhere in the U.S.

Full time employment, Monday - Friday, 40 hours per week.

Master's degree in Computer Science, Business Analytics, or another data engineering-related field and 3 years of related work experience. Alternatively, will accept a Bachelor's degree in Computer Science, Business Analytics, or another data engineering-related field and 5 years of progressive, post-baccalaureate related work experience.

Must have 3 years of experience in each of the following:

• Querying, transforming, and validating healthcare claims data in relational and cloud-based databases;

• Developing ETL pipelines and automating data workflows for healthcare claims data;

• Designing and building automated ETL workflows for structured and semi-structured healthcare data using Python and AWS Glue, along with AWS services;

• Implementing structured development workflows and automated deployment processes to maintain scalable, reliable data pipelines and cloud infrastructure; and

• Using Tableau for data visualization and reporting on healthcare data, including publishing dashboards and managing data sources and user permissions in a Tableau Cloud environment.

Must have 1 year of experience in each of the following:

• Modernizing legacy pipelines and implementing healthcare-specific data governance best practices; and