About the Role
We’re looking for a hands-on Data Engineer / Analyst with strong SAS, Python, and SQL skills to support and enhance our healthcare analytics platforms. You’ll split your time between production support (stability, incident resolution, performance tuning) and development (building data pipelines, models, and analytics solutions). You’ll work with large datasets (millions of rows) and collaborate closely with business stakeholders to translate requirements into robust, scalable solutions.
Key Responsibilities
Production Support (≈50%)
- Monitor, troubleshoot, and resolve issues across SAS jobs, Python scripts, and SQL queries / processes.
- Own incident triage, root cause analysis, and preventive fixes; maintain runbooks and support documentation.
- Optimize long-running jobs and SQL queries; manage job scheduling and dependencies.
- Ensure data quality, lineage visibility, and SLAs for data availability and reports.
Development (≈50%)
Design and build data pipelines to ingest, transform, and aggregate large datasets (structured / semi-structured).Develop reusable data assets (views, tables, marts) and analytics-ready datasets.Implement business logic, validations, and performance best practices across SAS / Python / SQL.Partner with business users to gather requirements, define acceptance criteria, and deliver features iteratively.Contribute to CI / CD, version control (., Git), and environment promotion (dev → test → prod)