Data Governance Lead
J
JobgetherData Governance
Based in United StatesFull-TimeLead
Salary not disclosed
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Job Details
- Experience
- 8+ years of experience across data governance, data platform engineering, data architecture, analytics engineering, or related disciplines; 3+ years of experience leading governance programs, stewardship models, or cross-functional data operating frameworks.
- Required Skills
- KafkaData engineering
Requirements
- Bachelor’s degree or equivalent professional experience.
- 8+ years of experience across data governance, data platform engineering, data architecture, analytics engineering, or related disciplines.
- 3+ years of experience leading governance programs, stewardship models, or cross-functional data operating frameworks.
- Proven experience building and operating governance capabilities within modern cloud data platforms.
- Hands-on experience implementing platform governance controls, including RBAC, row-level security, column-level security, classification tags, masking policies, and access management.
- Experience implementing and operating data catalog and lineage solutions, including metadata management and automated lineage capture.
- Experience defining and maintaining data quality rules within transformation pipelines and managing quality remediation processes.
- Experience governing event schemas and contracts in streaming or messaging environments such as Kafka, MuleSoft, or similar technologies.
- Experience defining data product governance standards, including ownership models, certification criteria, documentation requirements, discoverability, and lifecycle management.
- Experience designing governance controls for AI and agent-based workflows, including data usage policies, access controls, traceability, and auditability.
- Experience working directly with engineering teams through development cycles, design reviews, and implementation activities.
- Strong understanding of core governance disciplines, including data ownership, stewardship, metadata, lineage, cataloging, classification, retention, and policy adoption.
Responsibilities
- Build and operate an enterprise data catalog by onboarding domains and data products, defining metadata standards, and ensuring complete documentation of ownership, SLAs, classification, lineage, and contracts.
- Implement automated data lineage capabilities across ingestion pipelines, transformation layers, and published data products.
- Define and maintain data quality frameworks by creating validation rules, integrating checks into pipelines, configuring alerts, and managing remediation workflows.
- Configure and enforce platform-level security and governance controls, including role-based access, row- and column-level security, classification tags, masking policies, and access enforcement.
- Design and implement self-service access workflows that allow users to discover, request, and obtain appropriately scoped data access.
- Establish event contract governance practices, including schema standards, registries, retention policies, and access controls for streaming data environments.
- Develop governance dashboards and operational metrics covering stewardship participation, metadata completeness, lineage coverage, quality performance, policy adoption, and access request SLAs.
- Define and execute the enterprise data governance strategy, roadmap, standards, and operating model in alignment with business and platform objectives.
- Design governance controls supporting AI and agent-based use cases, including data usage guardrails, sensitive data protection, traceability, and auditability.
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