Key Responsibilities

Develop and own the enterprise data governance framework, including policies, standards, metadata strategy, and data stewardship processes.
Lead governance across cloud and analytics platforms with priority on Databricks and Unity Catalog, followed by AWS data services and Dataiku.
Define catalog structure, classification models, tagging, and access rules across multiple business domains.
Implement metadata management, lineage tracking, and data quality controls to improve trust and usability.
Drive unification of data across fragmented systems by designing scalable models, harmonized definitions, and reusable governance patterns.
Partner with cross-functional teams to ensure data privacy, security, and regulatory compliance (e.g., PII, GxP, HIPAA where applicable).
Oversee data access controls, entitlements, and policy enforcement across analytic environments.
Establish processes for issue management, remediation, and continuous improvement.
Mentor data stewards and support adoption of governance standards across business teams.
Support platform modernization and enable analytics, AI/ML, automation, and self-service use cases.

Required Skills & Experience

7+ years in data governance, data management, or enterprise data architecture.
Hands-on expertise with Databricks and Unity Catalog (catalog design, access policies, lineage, classification/tagging) as the primary platform requirement.
Experience with AWS data services (e.g., S3, Glue, Lake Formation, Redshift, IAM).
Experience with data governance workflows, tooling, and model management.
Strong understanding of MDM, metadata management, and data quality frameworks.
Proven success governing data across fragmented systems, complex pipelines, and multi-cloud or hybrid environments.
Familiarity with data privacy and compliance (PII, PHI, GxP, GDPR, etc.).
Ability to work across business and technical teams, influence without authority, and build alignment.
Excellent communication skills, with ability to translate governance concepts for non-technical audiences.

Preferred Qualifications

Experience in life sciences, healthcare, or regulated industries.
Background with product-oriented data platforms or customer-facing data services.
Knowledge of workflow tools (Jira, Confluence) and governance platforms (Collibra, Alation, data.world preferred but not required).
Certifications in Databricks, AWS, or data governance frameworks