Director, Data Management (EIM / Health Plan Analytics / AI & ML) - REMOTE

Director, Data Management (EIM)

Job Summary

The Director, Data Management is a senior leadership role within Molina Healthcare responsible for enterprise data management strategy, delivery, and modernization across core health plan domains . This role leads the design, integration, and operation of data platforms that support Medicaid, Medicare, Marketplace, and other payer lines of business , with a strong emphasis on Databricks-based lakehouse architecture, AI-enabled data management, and cloud platform cost optimization (FinOps) .

This leader owns end-to-end data domain delivery , including ingestion, integration, governance, quality, analytics enablement, and operational reliability for critical healthcare data such as claims, clinical, provider, member, authorizations, encounters, quality, and financial data . The role partners closely with Clinical, Operations, Finance, Compliance, Security, and Enterprise Architecture to ensure data solutions are secure, compliant, scalable, and aligned to Molina's business objectives and regulatory obligations .

The Director balances near-term delivery commitments with long-term platform strategy, ensuring Molina's data ecosystem enables analytics, reporting, regulatory submissions, value-based care, and AI/ML use cases.

Key Responsibilities

Healthcare Data Domain Leadership

• Lead delivery and ongoing management of core payer data domains , including but not limited to:

• Claims, Encounters, Authorizations

• Clinical and Utilization Management data

• Provider, Network, and Contract data

• Member, Eligibility, and Enrollment data

• Quality, HEDIS, and Regulatory reporting data

• Establish clear data domain ownership, stewardship, and accountability models across business and IT.

• Ensure data consistency, quality, lineage, and traceability required for regulatory audits and reporting .

Databricks & Data Platform Modernization

• Drive Molina's Databricks lakehouse strategy , including ingestion, transformation, analytics, ML enablement, and downstream consumption.

• Lead modernization from legacy data warehouses, marts, and custom pipelines to cloud-native, scalable data platforms .

• Define and enforce platform standards for performance, security, availability, resiliency, and operational excellence .

AI-Enabled Data Management

• Enable AI and ML-ready data foundations , including governed datasets, feature stores, and reusable data products.

• Promote use of automation and AI-assisted capabilities for data quality monitoring, anomaly detection, metadata enrichment, and observability.

• Partner with analytics, reporting, and AI teams to accelerate insights that support clinical outcomes, cost management, and operational efficiency .

Enterprise Integration & Data Exchange

• Oversee enterprise data integration and data movement patterns , including batch, near-real-time, streaming, APIs, and industry standards (e.g., 837/835/278, FHIR where applicable).

• Ensure secure, compliant data exchanges with internal systems and external vendors, partners, and delegated entities .

• Establish clear ownership and operating models for inbound and outbound data pipelines.

FinOps & Platform Cost Management

• Lead cloud and data platform financial management (FinOps) , including Databricks usage, storage, and compute optimization.

• Establish cost transparency, forecasting, and governance to balance performance, scalability, and cost efficiency .

• Drive accountability for platform usage across teams and domains.

Delivery, Governance & Risk Management

• Partner with EPMO, business leaders, and IT stakeholders to manage roadmaps, priorities, dependencies, and delivery commitments .

• Ensure adherence to HIPAA, CMS, state Medicaid, and internal security and compliance requirements .

• Identify and mitigate data, platform, and delivery risks impacting business continuity and regulatory obligations.

Leadership & Team Development

• Build, lead, and mentor data engineering, platform, and integration teams .

• Establish clear performance expectations, metrics, and career development paths.

• Champion modern engineering practices, documentation, and operational discipline.

Required Knowledge, Skills & Experience

Required

• 10+ years of experience in healthcare data management, data engineering, or analytics , with direct experience in a payer / managed-care organization .

• Strong understanding of health plan operations and data , including claims, encounters, authorizations, provider, member, and clinical data.

• Proven leadership experience delivering enterprise-scale data platforms and integrations .

• Hands-on experience with Databricks and Azure cloud data platforms .

• Experience operating in highly regulated healthcare environments (HIPAA, CMS, state Medicaid).

• Demonstrated ability to lead cross-functional teams and manage complex stakeholder relationships.

Preferred

• Experience supporting Medicaid, Medicare, Marketplace , or multi-LOB health plans.

• Experience enabling AI/ML initiatives in healthcare.

• Strong background in FinOps, cloud cost governance, and optimization .

• Familiarity with healthcare data standards and integrations (EDI, FHIR, HL7).

• Prior experience in Data Engineering and Data Management

Leadership Expectations

• Acts as a healthcare data thought leader within Molina.

• Treats data as a strategic enterprise asset supporting clinical quality, regulatory compliance, and financial performance.

• Drives results through collaboration, accountability, and disciplined execution .

• Promotes standardization, reuse, and long-term sustainability of Molina's data ecosystem.To all current Molina employees: If you are interested in applying for this position, please apply through the intranet job listing.Molina Healthcare offers a competitive benefits and compensation package. Molina Healthcare is an Equal Opportunity Employer (EOE) M/F/D/V.

Pay Range: $117,731 - $229,576 / ANNUAL

*Actual compensation may vary from posting based on geographic location, work experience, education and/or skill level.