Key skills
Data EngineeringEnterprise Data Lifecycle OrchestrationSDLCJiraMulti-Cloud ArchitectureCloud Data PipelinesGoogle Cloud Platform (GCP)DataFormDataFlowSecurity ComplianceHealthcare Data ProductsPerformance EngineeringQA ValidationRelease ManagementChange Approval Board (CAB) ProcessDataOpsJavaScriptPythonApache SparkSQLStored ProceduresCI/CDApache AirflowJenkinsAI/ML InfrastructureGenerative AIVector DatabasesGraph DatabasesLarge Language Model (LLM) OrchestrationHealthcare Data StandardsHL7FHIRElectronic Health Records (EHR) SystemsHealthcare Regulatory RequirementsFinOpsCloud Cost OptimizationCloud Data WarehousingBigQueryAIData WarehousingSparkAirflowGCPLeadershipMentoring
About this role
Ascension is a leading nonprofit Catholic health system empowering its associates to reimagine healthcare. The Manager of Data Engineering will oversee the end-to-end SDLC for data infrastructure, govern the design and optimization of data pipelines, and cultivate a high-performance engineering culture through technical leadership.
Responsibilities:
- Direct the end-to-end SDLC for high-scale data infrastructure, translating complex product roadmaps into executable technical workstreams while maintaining strict oversight of iteration goals, sprint metrics in Jira, and program-level delivery commitments
- Govern the design, development, and optimization of distributed data pipelines on Cloud environments - GCP preferred, leveraging DataForm or DataFlow to drive automation, code quality, and stringent security compliance across all HealthCare Analytical and Operational data products
- Architect and validate comprehensive testing frameworks—including functional, integration, and performance testing—to ensure production stability and facilitate seamless, high-quality knowledge transfers during technical handoffs to DataOps teams
- Optimize workgroup throughput by conducting forensic audits of technical estimations and story points, aggressively neutralizing cross-functional technical dependencies, and managing MSP/augmentation partner deliverables to sustain high-velocity engineering operations
- Cultivate a high-performance engineering culture by mentoring technical leads on data ingestion concepts, leveraging newer technologies like JavaScript, Python, and Spark as well as traditional database oriented toolsets of SQL scripts and Stored Procedures, while iteratively optimizing CI/CD workflows (Airflow, Jenkins) to enhance the scalability, reliability, and innovative capacity of the data ecosystem
Requirements:
- High School diploma equivalency with 3 years of cumulative experience OR Associate's degree/Bachelor's degree with 2 years of cumulative experience OR 7 years of applicable cumulative job specific experience required
- 3 years of leadership or management experience preferred
- Direct the end-to-end SDLC for high-scale data infrastructure
- Govern the design, development, and optimization of distributed data pipelines on Cloud environments - GCP preferred
- Architect and validate comprehensive testing frameworks—including functional, integration, and performance testing
- Optimize workgroup throughput by conducting forensic audits of technical estimations and story points
- Cultivate a high-performance engineering culture by mentoring technical leads on data ingestion concepts
- Hands-on experience architecting data foundations for Generative AI applications
- Deep understanding of clinical data standards (HL7, FHIR) experience with EHR systems
- Proven track record of implementing cost-optimization strategies for cloud data warehousing