Principal, Data Governance Platforms

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 platforms operate at 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, and operated , 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. The Principal leads through deep technical expertise , architectural ownership, and cross-functional engineering collaboration.

Required

Preferred

Required

Preferred

Required

Preferred

Technical / Role-Specific Skills

• Metadata Management & Data Catalog Platforms: Hands-on expertise with 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 Reltio, Informatica MDM, or Profisee ; understanding of matching, merging, and golden record architecture
• Data Quality & Observability Tools: Proficiency with data quality platforms including Acceldata or Informatica Data Quality; ability to configure rules, scoring frameworks, and alerting at scale
• Data Pipeline & Integration Design: Solid grounding in data engineering practices including ETL/ELT pipelines, API integration, and cloud-native data platforms (Azure Data Factory, Databricks, or equivalent)
• Cloud Data Platforms & Architecture: Experience architecting governance solutions within enterprise cloud ecosystems; working knowledge of cloud security controls, access management, and data classification
• SQL & Data Querying: Proficiency in SQL for data validation, quality rule development, and governance investigation workflows
• Technical Documentation & Architecture Communication: Ability to produce clear platform architecture documents and translate technical design decisions for non-technical governance stakeholders

Licensure

Essential Physical Functions

Requirements

• Metadata Management & Data Catalog Platforms: Hands-on expertise with 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 Reltio, Informatica MDM, or Profisee ; understanding of matching, merging, and golden record architecture
• Data Quality & Observability Tools: Proficiency with data quality platforms including Acceldata or Informatica Data Quality; ability to configure rules, scoring frameworks, and alerting at scale
• Data Pipeline & Integration Design: Solid grounding in data engineering practices including ETL/ELT pipelines, API integration, and cloud-native data platforms (Azure Data Factory, Databricks, or equivalent)
• Cloud Data Platforms & Architecture: Experience architecting governance solutions within enterprise cloud ecosystems; working knowledge of cloud security controls, access management, and data classification
• SQL & Data Querying: Proficiency in SQL for data validation, quality rule development, and governance investigation workflows
• Technical Documentation & Architecture Communication: Ability to produce clear platform architecture documents and translate technical design decisions for non-technical governance stakeholders