Principal, Data Governance Platforms

About this role

Alignment Health is breaking the mold in conventional health care, committed to serving seniors and those who need it most: the chronically ill and frail. It takes an entire team of passionate and caring people, united in our mission to put the senior first.We have built a team of talented and experienced people who are passionate about transforming the lives of the seniors we serve. In this fast-growing company, you will find ample room for growth and innovation alongside the Alignment Health community. Working at Alignment Health provides an opportunity to do work that really matters, not only changing lives but saving them. Together.
The Principal, Data Governance Platforms is the organization's technical authority for enabling enterprise data governance through purpose-built technology platforms and data management capabilities, spanning metadata, master data, data quality, and lineage. Working at the intersection of data engineering, enterprise architecture, and governance strategy, this role ensures that governance is not just a policy — it is a platform capability that operates reliably at scale. Collaborating closely with data engineering teams, enterprise architects, and governance operations counterparts, the Principal designs and implements the technical infrastructure that makes governance measurable, auditable, and sustainably automated.
JOB DUTIES / RESPONSIBILITIES

1. Governance Platform Strategy & Architecture
Define the technology architecture for enterprise data governance capabilities — including metadata management, MDM, data quality, and lineage — ensuring the platform strategy supports both current operational requirements and future AI and analytics ambitions. Align platform decisions with enterprise data architecture principles and cloud ecosystem standards.

2. Platform Implementation & Lifecycle Operations
Lead and execute the implementation of governance platforms, managing configuration, integration, testing, and go-live activities in partnership with engineering and IT teams. Ensure platformsoperateat production-grade standards for performance, availability, and data integrity across all governance use cases.

3. Data Lifecycle Capability Enablement
Enable governance-aligned data integration, transformation, enrichment, and standardization capabilities by embedding governance controls directly into data pipelines and processing workflows. Partner with data engineering to ensure governance requirements are built into platform architecture from the ground up, not layered on afterward.

4. Data Integration & Workflow Automation
Design and implement automated governance workflows — including data quality rule execution, metadata harvesting, lineage capture, and MDM matching — within data pipelines and platform ecosystems. Reduce manual governance overhead by embedding automation at the point of data creation and movement.

5. Lineage, Observability & Traceability
Enable comprehensive visibility into data flows, system dependencies, and transformation logic to support impact analysis, audit readiness, and root cause investigation. Maintain lineage capabilities that span the full data ecosystem from source systems through to downstream consumption in analytics, reporting, and AI model inputs.

6. Technical Governance Standards & Documentation
Establish and maintain technical standards for how governance platforms are configured, integrated, andoperated, ensuring consistency across platform implementations and enabling knowledge transfer to engineering teams. Produce platform architecture documentation that serves both technical teams and governance stakeholders.

7. Collaboration with Engineering & Enterprise Architecture
Partner closely with data engineering, cloud infrastructure, and enterprise architecture teams to ensure governance platforms are integrated into the broader data and technology ecosystem. Translate governance business requirements into scalable technical solutions that align with organizational standards and security controls.

SUPERVISORY RESPONSIBILITIES

This is an individual contributor role with no direct supervisory responsibilities. ThePrincipalleads through deep technicalexpertise, architectural ownership, and cross-functional engineering collaboration.

JOB REQUIREMENTS

Experience

Required:

• 10+ years of experience in data engineering, data architecture, or data governance platform implementation

• Demonstrated experience implementingand operatingenterprise-scale data governance or data management platforms

• Experience integrating governance tooling into cloud-based data platforms and pipelines

• Healthcare industry experience preferred; Medicare Advantage or payer experience is a significant differentiator

• Experience implementing MDM, data catalog, or data quality platforms in a regulated healthcare environment

Preferred:

• Familiarity with HIPAA technical safeguard requirements as they apply to data platform architecture

Education

Required:

• Bachelor's degree in Information Management, Information Systems, Computer Science,Data Engineering,Business, Health Informatics, or a related field

Preferred:

• Master's degree in a relevant technical discipline

Training

Required:

• Hands-on platform experience with at least one enterprise data catalog (e.g., Purview, Alation), one MDM platform (e.g., Reltio, Informatica,Profisee), and one data quality/observability tool (e.g.,Acceldata, Informatica DQ)

• HIPAA technical compliance knowledge as it applies to data platform architecture

Preferred:

• Cloud platform certification (Azure, AWS, or GCP); Microsoft Purview or Databricks certification

SKILLS & COMPETENCIES

Technical / Role-Specific Skills

• Metadata Management & Data Catalog Platforms:Hands-onexpertisewith Microsoft Purview or Alation for metadata ingestion, cataloging, lineage capture, and governance policy enforcement

• Master Data Management Systems:Deep implementation experience with MDM platforms such as…