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Key Responsibilities and Required Skills for Data Governance Consultant

💰 $ - $

Data GovernanceConsultingData Management

🎯 Role Definition

A Data Governance Consultant designs, implements, and operationalizes enterprise data governance frameworks that ensure data is accurate, discoverable, secure, and fit-for-purpose. Working at the intersection of business, IT, and compliance, the consultant leads stakeholder engagement, defines policies and standards, implements data catalog and metadata management solutions, and drives measurable improvements in data quality, lineage, privacy controls, and master data management (MDM). Typical deliverables include data governance strategy, policy library, stewardship model, data dictionaries, data classification, data lineage documentation, and tooling recommendations (e.g., Collibra, Alation, Informatica, Azure Purview).

Keywords: data governance, data quality, metadata management, data catalog, data stewardship, data privacy, GDPR, CCPA, MDM, data lineage, data classification, governance framework, Collibra, Alation, Azure Purview, master data, data standards, policy.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Data Analyst transitioning to governance responsibilities (data quality and metadata workstreams).
  • Business Analyst or Business Systems Analyst with domain knowledge and stakeholder engagement experience.
  • Master Data Management (MDM) specialist, data steward, or compliance analyst moving into governance consulting.

Advancement To:

  • Senior Data Governance Consultant / Lead Data Governance Architect.
  • Data Governance Manager or Head of Data Governance.
  • Chief Data Officer (CDO) or Director of Data Management.

Lateral Moves:

  • Data Privacy / Compliance Consultant (GDPR, CCPA).
  • Data Quality Lead or Data Product Owner.
  • Enterprise Data Architect or Metadata Architect.

Core Responsibilities

Primary Functions

  • Develop and implement a scalable enterprise data governance framework that defines roles, responsibilities, workflows, policies, and operating model to support business initiatives and compliance requirements.
  • Conduct stakeholder assessments and governance maturity assessments across business units to identify gaps, prioritize use cases, and create a phased roadmap and business case for data governance adoption.
  • Design and operationalize a data stewardship program—recruiting, training and enabling business and technical stewards; defining stewardship workflows; and establishing accountability for data domains and master data entities.
  • Define, document, and socialize enterprise data policies, standards, data definitions (business glossaries), and data classification schemes to ensure consistent understanding and use of data across the organization.
  • Lead the implementation and configuration of data governance and metadata management tools (e.g., Collibra, Alation, Informatica EDC, Azure Purview), including cataloging, metadata harvesting, data lineage capture, and role-based access controls.
  • Build and maintain a business glossary and metadata repository that maps critical data assets, owners, stewards, quality rules, transformation logic, and downstream consumers to enable discoverability and trust.
  • Establish and operationalize data quality frameworks—define data quality metrics, SLAs, measurement approaches, rule-based validations, and monitoring dashboards in collaboration with data engineering and BI teams.
  • Design and document end-to-end data lineage to demonstrate data provenance, transformations, and downstream usage for analytics, regulatory audits, and impact analysis.
  • Partner with legal, privacy, and security teams to assess regulatory and compliance requirements (GDPR, CCPA, HIPAA, SOC2), define privacy-by-design controls, data retention policies and data subject access request processes.
  • Conduct data profiling and root-cause analysis to identify systemic data issues and collaborate with source system owners, ETL developers, and product teams to remediate upstream quality problems.
  • Create and manage governance KPIs and performance reporting (data quality scores, stewardship completion rates, catalog adoption metrics) and present measurable business outcomes to senior stakeholders.
  • Facilitate governance councils, working groups, and executive steering committees to prioritize data initiatives, approve standards, and resolve cross-functional data conflicts.
  • Develop role-based training, onboarding materials, and playbooks for data stewards, data owners, and users to institutionalize governance processes and support cultural adoption.
  • Design master data management (MDM) strategies including hub-and-spoke models, golden record creation, matching and merging rules, and integration patterns to ensure a single source of truth for critical domains.
  • Lead data classification and sensitive data discovery projects—identify PII/PHI, apply masking/tokenization strategies, and recommend access control and encryption approaches in partnership with security teams.
  • Support data product thinking: help define data product owners, SLAs, documentation, and service-level agreements to treat data as a product and improve data usability.
  • Establish change management and communication plans to drive adoption—create newsletters, roadshows, governance scorecards, and success stories that show ROI and business impact.
  • Provide advisory services for data architecture and integration decisions that impact governance, including metadata capture points, event-driven vs batch patterns, and API governance.
  • Create and test governance operating procedures for incident management, data remediation playbooks, and escalation paths to ensure timely resolution of data incidents.
  • Perform vendor evaluations, RFPs, and proof-of-concepts for data governance, catalog, metadata, and MDM platforms; create vendor selection criteria and value assessments.
  • Lead cross-functional implementation projects with agile practices—write user stories, prioritize sprint backlogs, and validate acceptance criteria for governance tooling and automation.
  • Prepare audit-ready documentation and evidence of governance activities, including data policy sign-offs, stewardship logs, and controls testing for internal and external audits.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis to help business stakeholders understand data availability and limitations.
  • Contribute to the organization's data strategy and roadmap by aligning governance initiatives with business priorities and analytics goals.
  • Collaborate with business units to translate data needs into engineering requirements and acceptance criteria for pipeline and model development.
  • Participate in sprint planning and agile ceremonies within the data engineering and analytics delivery teams to embed governance controls into development lifecycles.
  • Mentor junior governance analysts and provide subject matter expertise for cross-functional projects.
  • Assist in building templates for data contracts, data sharing agreements, and data usage policies to govern third-party data exchanges.
  • Help assess and prioritize technical debt related to metadata, documentation gaps, and tooling improvements across the data stack.
  • Coordinate with cloud and platform teams to ensure metadata capture and governance capabilities are embedded in data platforms (AWS, Azure, GCP).
  • Support periodic readiness checks for regulatory initiatives and data-related audits; collate artifacts and evidence for compliance reviews.
  • Contribute to value realization tracking by quantifying improvements (reduced incident rates, faster analytics delivery, improved data quality) attributable to governance activities.

Required Skills & Competencies

Hard Skills (Technical)

  • Strong knowledge of data governance frameworks, best practices, and operating models (e.g., DAMA, DCAM).
  • Experience implementing and configuring data governance, metadata management, and data catalog tools (Collibra, Alation, Informatica EDC, Azure Purview, Atlan).
  • Proficiency with data profiling and quality tools and approaches; ability to author data quality rules and SLA definitions.
  • Practical understanding of data lineage, ETL/ELT processes, data pipelines, and the ability to capture lineage from source to target.
  • Familiarity with master data management (MDM) concepts, survivorship logic, matching/merging algorithms, and MDM platforms (Informatica MDM, Reltio, Stibo).
  • Working knowledge of data privacy regulations and controls (GDPR, CCPA, HIPAA), including anonymization, masking, and retention policy design.
  • Basic SQL skills for data profiling, querying, and validating data; familiarity with relational and big data stores (Snowflake, Redshift, Azure Synapse, Databricks).
  • Understanding of cloud data platforms and metadata integration points in AWS, Azure, or GCP environments.
  • Experience with data modeling concepts and business glossary creation; ability to translate business terms to technical artifacts.
  • Capability to evaluate vendors, design RFPs, conduct POCs, and recommend governance tooling based on scale and requirements.
  • Familiarity with API metadata, event-driven architectures, and cataloging streaming data sources (Kafka, Kinesis) is a plus.
  • Experience creating dashboards and governance reporting using BI tools (Power BI, Tableau, Looker) to communicate metrics and adoption.

Soft Skills

  • Strong stakeholder management: ability to influence at executive and operational levels and build cross-functional consensus.
  • Excellent communication and presentation skills to socialize policies, training materials, and governance KPI reports.
  • Analytical and problem-solving mindset with attention to detail and ability to perform root-cause data investigations.
  • Project and program management capability: planning, prioritization, and delivering governance initiatives on time and within scope.
  • Change management and facilitation skills to drive adoption of governance practices across diverse teams.
  • Customer-focused consulting approach with the ability to translate technical concepts into business value.
  • Collaborative mindset and ability to work effectively with data engineers, architects, product owners, security and legal teams.
  • Adaptability and resilience in complex, ambiguous environments where governance maturity varies across domains.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor’s degree in Information Systems, Computer Science, Business Administration, Data Science, Information Management, or related field.

Preferred Education:

  • Master’s degree in Information Management, Data Science, Business Analytics, or MBA with data governance coursework.
  • Professional certifications such as Certified Data Management Professional (CDMP), Collibra Certification, or DAMA certification are advantageous.

Relevant Fields of Study:

  • Information Systems / Information Management
  • Computer Science / Software Engineering
  • Business Analytics / Data Science
  • Business Administration with analytics or IT focus
  • Data Governance / Compliance and Risk Management

Experience Requirements

Typical Experience Range:

  • 3–7 years in data governance, data management, MDM, or related data roles for mid-level consultant positions.
  • 7+ years for senior consultant or lead positions, including demonstrated project leadership, tool implementations, and stakeholder management.

Preferred:

  • Proven track record implementing enterprise data governance programs, data catalog deployments, or MDM initiatives across multiple domains.
  • Experience in regulated industries (financial services, healthcare, telecommunications, government) where data privacy and lineage requirements are stringent.
  • Prior consulting or client-facing experience delivering governance transformation, change management, and measurable business outcomes.
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