Key Responsibilities and Required Skills for Data Governance Specialist

🎯 Role Definition

The Data Governance Specialist is responsible for designing, implementing, and operating enterprise data governance frameworks that ensure data is discoverable, trusted, compliant, and used responsibly. This role partners with business stakeholders, data stewards, data engineers, security and legal teams to define policies, enforce data quality standards, manage metadata and lineage, and enable self-service analytics while reducing risk and ensuring regulatory compliance (GDPR, CCPA, HIPAA where applicable).

Key outcomes include improved data quality scores, consistent metadata across systems, documented data lineage, reduction in data-related risks, and measurable increases in trusted self-service analytics adoption.

📈 Career Progression

Typical Career Path

Entry Point From:

Data Analyst transitioning into governance and policy work
Business Analyst or Business Systems Analyst with data-focused responsibilities
IT Auditor, Compliance Analyst or Risk Analyst with exposure to data controls
Data Steward or Data Quality Analyst moving into enterprise governance

Advancement To:

Data Governance Manager / Lead
Head of Data Management or Director, Data Operations
Chief Data Officer (CDO) or Senior Data Privacy & Compliance Lead
Enterprise Data Architect with governance specialization

Lateral Moves:

Data Steward / Data Quality Lead
Metadata Management or Data Catalog Administrator
Business Intelligence Manager or Analytics Product Owner

Core Responsibilities

Primary Functions

Develop, document and operationalize a comprehensive enterprise data governance framework, including governance operating model, roles and responsibilities (data owners, stewards), decision rights, and escalation paths to ensure consistent data stewardship across business units.
Lead the design, roll-out and maintenance of data policies, standards and procedures (data classification, data access, data retention, data lineage, metadata standards) and drive adoption through communication, training and governance councils.
Establish and run a cross-functional Data Governance Council and working groups to prioritize governance initiatives, resolve data issues, and align governance activities with business objectives and regulatory requirements.
Define and implement data stewardship programs, recruiting and enabling business data stewards with clear RACI, onboarding, KPIs and training materials to operationalize accountability for data quality and policy compliance.
Create and manage enterprise taxonomy and data classification schemes to ensure consistent labeling of sensitive and regulated data, enabling effective access controls, masking, and retention enforcement.
Implement and configure data governance and metadata management tools (e.g., Collibra, Alation, Informatica Axon, Talend, Azure Purview), including metadata harvesting, glossary creation, stewardship workflows, and role-based access.
Design and execute data quality frameworks and measurement programs (profiling, rules, thresholds, dashboards) in partnership with data engineering to detect, triage and remediate data quality issues with clear SLAs and business impact tracking.
Map and document end-to-end data lineage across source systems, ETL/ELT pipelines, data lakes and reporting layers to support impact analysis, change management, and regulatory audits.
Lead privacy and compliance initiatives related to personal and sensitive data, supporting GDPR/CCPA/CPRA assessments, data subject access requests (DSARs), privacy-by-design reviews and data protection impact assessments (DPIAs).
Partner with security, legal and risk teams to translate data governance requirements into access controls, encryption, pseudonymization strategies and data retention policies to mitigate data risk.
Develop and maintain a centralized data catalog and business glossary that facilitates data discoverability, business context, data owners, quality scores, and approved uses for analytics and reporting.
Establish metrics and KPIs for governance effectiveness (e.g., data quality score improvements, time-to-resolve data issues, percentage of assets cataloged) and report program ROI and risk reduction to senior leadership.
Drive data onboarding and offboarding processes for new data sources and third-party integrations, ensuring metadata capture, classification, contract & vendor controls, and data sharing agreements are in place.
Define and enforce master data management (MDM) patterns and stewardship processes to ensure consistent reference data, golden records, and authoritative sources across domains (customers, products, suppliers).
Collaborate with data engineering and platform teams to bake governance controls into data pipelines (automated profiling, lineage capture, schema validation, policy enforcement) for scalable, automated governance.
Conduct regular data risk assessments and audits to identify gaps in controls, compliance exposure, or operational weaknesses; create remediation plans and track closure.
Facilitate cross-functional workshops and stakeholder interviews to capture business rules, critical data elements (CDEs), and reporting dependencies to inform governance priorities and roadmap.
Design and deliver training, communication campaigns and self-service guidance to increase adoption of governance tools, clarify responsibilities, and promote a data-literate culture across the organization.
Create and manage change control processes for critical data definitions, schemas and transformations; maintain version-controlled documentation and communicate impacts to dependent consumers.
Coordinate with BI and analytics teams to ensure governed datasets are accessible for self-service analytics while preserving controls for sensitive data through masking, aggregation or role-based views.
Support incident response for data breaches or policy violations, conducting root cause analysis, documenting lessons learned, and implementing corrective controls to prevent recurrence.
Continuously benchmark governance practices against industry frameworks and standards (DAMA-DMBOK, ISO 8000, NIST) and recommend improvements and tooling enhancements to mature the program.

Secondary Functions

Support ad-hoc data requests and exploratory data analysis.
Contribute to the organization's data strategy and roadmap.
Collaborate with business units to translate data needs into engineering requirements.
Participate in sprint planning and agile ceremonies within the data engineering team.
Maintain up-to-date documentation for governance processes, playbooks, and FAQs to support self-service adoption.
Assist with vendor evaluations, proof-of-concepts and procurement activities for governance, cataloging, and data quality tools.
Provide subject matter expertise for regulatory audits or external assessments related to data control environments.
Mentor junior staff and stewards on governance best practices, data modeling basics and tool usage.

Required Skills & Competencies

Hard Skills (Technical)

Proven experience implementing and operating enterprise data governance frameworks, policies and operating models.
Hands-on experience with data governance and metadata catalog tools such as Collibra, Alation, Informatica Axon, Microsoft Purview (Azure Purview), Talend, or AWS Glue Data Catalog.
Strong data quality management skills: profiling, rule authoring, monitoring, remediation workflows and DQ tooling (Informatica Data Quality, Talend, Great Expectations).
Proficiency in data lineage and metadata management concepts and tools; ability to capture lineage across ETL/ELT, streaming and analytics layers.
Understanding of master data management (MDM) principles, reference data governance and techniques for entity resolution and golden records.
Familiarity with data privacy and protection frameworks (GDPR, CCPA/CPRA, HIPAA) and experience supporting privacy assessments, DPIAs and DSAR processes.
Working knowledge of data security controls: role-based access control (RBAC), attribute-based access control (ABAC), encryption, masking and tokenization strategies.
Competency with SQL for data profiling, sampling and issue investigation; familiarity with Python or R for more advanced data analysis is advantageous.
Experience integrating governance controls into data platforms, cloud services and data pipelines (AWS, Azure, GCP) and understanding of modern data architectures (lakehouse, data mesh).
Ability to design and report governance metrics, dashboards and KPIs using BI tools (Tableau, Power BI, Looker) and to present program status to stakeholders.
Experience with regulatory compliance audits and preparing documentation, evidence and roadmaps to meet audit requirements.
Familiarity with data modeling concepts and enterprise information architecture to align governance to logical and physical data assets.
Vendor evaluation and POC experience for governance, catalog and quality tools with ability to define requirements and select fit-for-purpose solutions.

Soft Skills

Strong stakeholder management and executive communication skills — ability to influence cross-functional teams and present governance value to senior leadership.
Excellent interpersonal and facilitation skills for running councils, workshops and cross-team governance sessions.
Analytical mindset with problem-solving orientation; ability to translate business problems into practical governance controls and measurable outcomes.
Change management capability to drive adoption, build stewardship networks, and create cultural shifts toward data responsibility.
Project management and organizational skills: able to run multi-stream governance programs, prioritize initiatives, and meet delivery deadlines.
Detail-oriented with a strong bias for documentation, standards, and repeatable processes.
Diplomatic negotiator and consensus-builder who can balance risk mitigation with enabling business innovation.
Continuous learner mindset to keep pace with evolving regulations, tooling and industry best practices.

Education & Experience

Educational Background

Minimum Education:

Bachelor's degree in Computer Science, Information Systems, Data Science, Business Administration, Information Governance, or related field.

Preferred Education:

Master's degree or advanced certification in Data Management, Information Governance, Business Analytics, Law (privacy focus), or related discipline.
Relevant certifications such as CDMP (Certified Data Management Professional), DGSP (Data Governance and Stewardship Professional), Collibra Certification, or CIPP/CP (privacy certifications) are a plus.

Relevant Fields of Study:

Computer Science / Software Engineering
Information Systems / MIS
Data Science / Analytics
Business Administration / Finance
Information Governance / Legal (privacy & compliance)

Experience Requirements

Typical Experience Range: 3–8 years of progressive experience in data governance, data management, data quality, compliance or related roles.

Preferred:

5+ years implementing or running enterprise data governance programs with demonstrable outcomes.
Experience in regulated industries (finance, healthcare, insurance, telecommunications) or large-scale enterprise environments.
Proven track record integrating governance into modern data platforms and collaboration across engineering, analytics and business domains.