Data Governance Lead

About the Role

This is a hands-on technical leadership position responsible for defining and executing the data governance strategy, roadmap, standards, policies, procedures, and controls. The role requires deep expertise in Databricks (Unity Catalog) and Snowflake governance, combined with the ability to lead cross-functional initiatives and drive governance adoption across the organization.

Key Responsibilities

• Establish and facilitate Data Governance Councils, domain governance forums, and data stewardship programs
• Define roles and accountability for Data Owners, Data Stewards, Data Custodians, Data Product Owners, and platform teams
• Develop governance KPIs, maturity assessments, adoption metrics, control evidence, and executive reporting
• Drive governance-by-design across data products, Data Mesh, analytics, reporting, AI/ML, and data-sharing initiatives
• Lead cross-functional issue resolution, remediation prioritization, change management, training, and governance adoption

Databricks Implementation

• Design, configure, implement, and administer Unity Catalog for enterprise-scale governance
• Create and manage catalogs, schemas, managed and external tables, views, volumes, storage credentials, external locations, and workspace bindings
• Implement least privilege access using account groups, role-based access control, grants, ownership standards, and separation of duties
• Configure and validate table-level, row-level, and column-level security, dynamic views, masking patterns, and sensitive-data protection controls
• Write and review Databricks SQL, Spark SQL, PySpark, and Python for metadata analysis, quality controls, reconciliation, audit reporting, and governance automation
• Use system tables, audit logs, information schema, and lineage capabilities to monitor access, permissions, usage, data movement, and policy compliance
• Establish governance standards across Bronze, Silver, and Gold layers, including naming, tagging, classification, schema evolution, retention, certification, and lifecycle controls
• Implement data quality checks using SQL, PySpark, Lakeflow Pipelines expectations or equivalent framework capabilities
• Govern Delta Lake assets, Databricks workflows, notebooks, jobs, dashboards, data products, and secure data sharing through Delta Sharing
• Partner with platform engineering and DevOps teams to embed governance checks, access controls, testing, and evidence collection into CI/CD pipelines
• Troubleshoot access, metadata, lineage, data quality, and control issues across development, test, and production workspaces

Snowflake Implementation

• Configure Snowflake roles, grants, ownership, warehouses, databases, schemas, tables, views, and secure access patterns
• Implement role-based access control, tag-based masking policies, row access policies, secure views, classification, and object tagging
• Develop SQL-based metadata, data quality, reconciliation, access-review, and compliance-monitoring solutions
• Govern internal and external data sharing, data marketplace usage, retention, cloning, and lifecycle controls
• Support lineage and metadata integration between Snowflake and the enterprise data catalog
• Review query performance, access history, object dependencies, and control effectiveness to identify governance risks

Metadata, Catalog & Lineage

• Lead implementation and adoption of the data catalog and business glossary
• Define mandatory business, technical, operational, security, and quality metadata standards
• Establish ownership, stewardship, critical data element, business term, and data product registration processes
• Implement and validate end-to-end lineage, source-to-target traceability, dependency analysis, and change-impact assessment
• Define certification, endorsement, deprecation, and discoverability standards for trusted data assets

Data Quality & Observability

• Define the data quality framework, dimensions, thresholds, SLAs/SLOs, issue severity, escalation, and remediation processes
• Profile data and develop executable rules for accuracy, completeness, consistency, validity, uniqueness, integrity, and timeliness
• Implement automated quality monitoring, scorecards, exception handling, control evidence, and trend reporting
• Lead root-cause analysis and coordinate remediation with source systems, engineering teams, and business owners
• Establish controls for critical data elements and certify data products based on measurable quality and governance criteria

Data Security, Privacy, Risk & Controls

• Define and enforce data classification, handling, retention, access, and sharing standards for public, internal, confidential, restricted, PII, PCI, and other sensitive data
• Partner with security and IAM teams to implement least privilege, segregation of duties, privileged access monitoring, periodic access reviews, and entitlement certification
• Establish preventive, detective, and corrective data controls with documented ownership, frequency, evidence, exceptions, and remediation
• Support applicable regulatory and control obligations such as PCI DSS, SOX, GLBA, GDPR, CCPA, and FedRAMP
• Support audits, risk assessments, control testing, issue management, policy exceptions, and regulatory evidence requests
• Ensure encryption, secrets management, key management, network security, logging, monitoring, and incident-response requirements are addressed with platform teams

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Management, Engineering, or a related discipline, or equivalent professional experience
• 10 years of experience in data governance, data management, data architecture, data engineering, information management, or related disciplines
• 5 years leading enterprise data governance programs or major governance workstreams in a complex, regulated organization
• Demonstrated recent hands-on implementation experience with Databricks, Unity Catalog, Snowflake, and advanced SQL
• Strong understanding of data governance operating models, metadata, lineage, data quality, privacy, security, controls, data lifecycle, and records-management concepts
• Experience translating policies and regulatory requirements into enforceable technical controls and measurable operating processes
• Strong executive communication, stakeholder influence, facilitation, conflict resolution, and team leadership skills
• Experience working in Agile delivery and collaborating with architecture, engineering, DevOps, product, security, risk, compliance, and audit teams

Leadership Competencies

• Strategic thinking with strong execution discipline
• Ability to lead through influence across business and technology organizations
• Clear executive communication and governance decision facilitation
• Strong analytical, problem-solving, and risk-based prioritization skills
• Ability to mentor data stewards, governance analysts, engineers, and platform teams
• Commitment to automation, measurable controls, accountability, and continuous improvement

Success Measures

• Governance operating model, ownership, stewardship, and decision rights established across priority domains
• Unity Catalog and Snowflake governance controls implemented and evidenced for in-scope data assets
• Critical data elements registered with accountable owners, definitions, lineage, classification, and quality rules
• Data quality scorecards and issue-remediation workflows operational for priority data products
• Improved catalog adoption, metadata completeness, access-review completion, and trusted-data certification
• Reduced audit findings, control gaps, policy exceptions, duplicate data assets, and unresolved quality issues

Recruiter Screening Statement: This is a hands-on technical leadership position, not a governance-policy-only role. Candidates must demonstrate recent experience configuring Databricks Unity Catalog, implementing Snowflake security and governance controls, and writing advanced SQL for data profiling, quality validation, reconciliation, metadata analysis, access reviews, and audit reporting.