Data Engineering Manager, Master Data

The California Department of Health Care Services (DHCS) is hiring a Data Engineering Manager, Master Data, to lead engineering delivery for its healthcare data platform. The role combines hands-on development with team leadership across data pipelines, master data management, reusable data products, quality controls, and production operations.

Responsibilities:

• Write, test, and ship production code for pipelines, data products, and master data services, and take assigned stories in each sprint
• Join the on-call rotation and work production incidents directly, through root-cause analysis and the fix
• Lead, mentor, and develop a team of data engineers, establishing clear expectations for technical quality, individual accountability, performance, and delivery
• Manage day-to-day engineering execution, including estimates, sprint planning, resource allocation, team capacity, technical dependencies, and delivery commitments
• Provide technical leadership through design reviews, code reviews, implementation guidance, and troubleshooting of complex data engineering challenges
• Establish and enforce engineering standards for code quality, documentation, performance, scalability, maintainability, and operational readiness
• Translate approved architecture designs and business requirements into executable engineering plans, identifying technical tradeoffs, dependencies, and implementation risks early
• Partner with the Director, Data Engineering and the Director, Data Portfolio to align engineering capacity, sequencing, and execution commitments with portfolio priorities
• Identify and resolve engineering risks, delivery constraints, and technical blockers, escalating decisions and dependencies when appropriate
• Build, test, deploy, and operate enterprise data ingestion, integration, transformation, and orchestration pipelines on a modern lakehouse platform, and lead the team doing the same work
• Implement layered data architectures, including bronze, silver, and gold data processing patterns, in accordance with established enterprise architecture standards
• Engineer and deliver reusable, governed data products, including curated datasets, analytical data models, and published data assets that support healthcare operations, quality measurement, reporting, and interoperability
• Implement quality controls, lineage, metadata, and operational monitoring to ensure data products are trusted, traceable, and fit for their intended use
• Optimize distributed data processing workloads for performance, scalability, reliability, and cost efficiency
• Build enterprise Master Data Management capabilities and support them in production, including Entity Resolution, master record management, data standardization, matching, consolidation, survivorship, and publication of authoritative master data
• Build and maintain engineering solutions supporting deterministic and probabilistic entity matching, identity reconciliation, and exception handling in accordance with approved requirements and technical designs
• Implement Reference Data capabilities, including controlled vocabularies, terminology mappings, reference data pipelines, and integration with enterprise data services
• Develop and maintain integrations that make mastered data and reference data consistently available to enterprise applications, analytical platforms, and downstream data products
• Partner with architecture, data governance, and business stakeholders to implement approved matching rules, mastering requirements, data quality controls, and stewardship workflows
• Establish and enforce automated testing, data validation, reconciliation, regression testing, and deployment verification practices across engineering solutions
• Embed data quality checks, metadata capture, lineage, auditability, and traceability into pipelines, master data services, and data products
• Implement consent-informed data access and sharing controls for protected health information in accordance with approved privacy policies, consent requirements, and enterprise security standards
• Ensure engineering solutions comply with established CI/CD processes, security requirements, change management procedures, and deployment controls
• Maintain production reliability through monitoring, observability, incident response, failure recovery, root-cause analysis, and continuous operational improvement
• Establish and monitor engineering performance indicators covering delivery predictability, pipeline reliability, data processing performance, defect rates, and operational effectiveness

Requirements:

• Must work on shore in the US
• We cannot sponsor or transfer an H1B Visa for this role
• 7+ years of progressive data engineering experience, including at least 3 years leading engineering teams while writing production code
• Has written and shipped production Spark, Python, and SQL code in the last 12 months on Databricks or a comparable lakehouse platform
• Can walk through a pipeline or data product they built: the design, the code, and how it ran in production
• Demonstrated ability to lead technical design reviews, evaluate engineering implementations, troubleshoot complex processing issues, and establish effective engineering practices
• Experience implementing layered (medallion) data architectures, ETL/ELT pipelines, distributed data processing, orchestration, and analytical data modeling
• Experience developing reusable data products, including curated datasets, data quality controls, metadata, lineage, and integration with downstream consumers
• Experience implementing or supporting enterprise Master Data Management capabilities, including entity resolution, record matching, master data integration, standardization, or survivorship
• Experience working with Medicaid, health plan, or payer data, including claims, encounters, eligibility, and member information
• Experience integrating healthcare data across enterprise systems using batch processing, APIs, and other data exchange mechanisms
• Experience managing engineering teams through agile delivery practices, including work estimation, sprint execution, capacity planning, and technical dependency management
• Experience implementing automated testing, data validation, reconciliation, CI/CD, and production monitoring for enterprise data solutions
• Working knowledge of HIPAA, 42 CFR Part 2, and technical controls for protecting sensitive healthcare information
• Experience delivering engineering solutions in multi-vendor environments with formal architecture, security, change management, and deployment controls
• Strong communication, problem-solving, and stakeholder management skills, with the ability to engage technical and nontechnical audiences
• Experience supporting a state Medicaid agency, public-sector healthcare program, or large-scale healthcare modernization initiative
• Experience implementing Entity Resolution solutions using deterministic or probabilistic matching, including match scoring, precision and recall evaluation, and identity reconciliation workflows
• Experience with enterprise MDM platforms, master patient indexes, golden record management, crosswalks, and master data publication services
• Experience with Databricks Delta Lake, Unity Catalog, Delta Live Tables or Lakeflow, and workflow orchestration
• Experience with healthcare interoperability standards, including HL7 FHIR and healthcare API integrations
• Experience with healthcare terminologies such as ICD-10-CM, CPT/HCPCS, LOINC, SNOMED CT, and RxNorm
• Experience preparing data for HEDIS or other healthcare quality measurement programs
• Experience with enterprise data governance and data quality platforms, including Collibra
• Experience implementing consent-aware data processing and access controls for regulated healthcare information