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data management consultant

title: Key Responsibilities and Required Skills for Data Management Consultant
salary: $ - $
categories: [Data Management, Consulting, Data Governance, MDM, Data Engineering]
description: A comprehensive overview of the key responsibilities, required technical skills and professional background for the role of a Data Management Consultant.
High-impact, SEO-optimized summary of a Data Management Consultant role: expert in data governance, master data management (MDM), data quality, metadata and lineage, cloud data platforms, and stakeholder-driven delivery. Ideal for candidates who design and implement enterprise data management frameworks, lead MDM implementations, improve data quality KPIs, and enable analytics through robust data architecture and stewardship programs.

🎯 Role Definition

As a Data Management Consultant you will partner with enterprise stakeholders to design, implement, and operationalize end-to-end data management capabilities — including data governance, master data management (MDM), data quality, metadata management, data lineage and cataloging. You will translate business requirements into technical designs, lead vendor/tool selection and implementation (e.g., Collibra, Alation, Informatica MDM, Reltio), drive data quality improvements, enable consistent master data across systems, and establish sustainable stewardship and operating models that support analytics, reporting and regulatory compliance. The role blends deep technical knowledge (data modeling, SQL, ETL/ELT, cloud) with strong consulting skills (workshops, roadmaps, change management, stakeholder alignment).

📈 Career Progression

Typical Career Path

Entry Point From:

  • Senior Data Analyst with governance or master data responsibilities
  • Data Engineer with experience in ETL/ELT and data pipelines
  • Business Analyst focused on data domains or regulatory reporting

Advancement To:

  • Lead Data Architect / Enterprise Data Architect
  • Head of Data Governance or Director of Data Management
  • Chief Data Officer (CDO) or Global Data Lead

Lateral Moves:

  • MDM Implementation Lead
  • Data Quality Manager
  • Data Governance Program Manager

Core Responsibilities

Primary Functions

  • Lead the design and implementation of enterprise data governance frameworks, creating policies, standards, and procedures that ensure data is accurate, accessible, and managed across the organization.
  • Manage end-to-end master data management (MDM) programs, including requirements gathering, solution design, configuration of MDM platforms (Informatica, Reltio, SAP MDG, Oracle MDM), and integration with source/target systems.
  • Build and implement data quality programs: define data quality rules, develop profiling processes, configure data quality tools, and deliver remediation plans that measurably improve critical data KPIs.
  • Conduct detailed data profiling and root-cause analysis to identify systemic data issues, propose corrective actions, and negotiate cross-functional remediation with data owners and IT teams.
  • Design canonical data and reference data models, including entity relationship diagrams, canonical data structures, and domain-driven models that support consistent master data usage across applications and analytics.
  • Define and document data lineage for critical business processes and data flows, leveraging metadata management and lineage tooling to support impact analysis, regulatory audits, and trust in analytics.
  • Lead vendor/tool selection and evaluation for data cataloging, data governance, MDM, and data quality technologies; prepare RFPs, run proof-of-concepts, and create business cases for investment.
  • Architect and oversee data integration patterns (ETL/ELT, API, streaming) to ensure master and reference data are synchronized across cloud and on-premise systems with transactional integrity and performance.
  • Establish and operationalize data stewardship models: recruit and train data stewards, define stewardship responsibilities, and create escalation paths and KPIs for ongoing stewardship activities.
  • Develop and maintain a prioritized data management roadmap aligned to business strategy, deliverables, regulatory timelines (GDPR, CCPA, HIPAA), and measurable outcomes.
  • Partner with analytics and BI teams to ensure trusted master data and high-quality datasets are available for reporting, machine learning, and self-service analytics initiatives.
  • Create and maintain enterprise metadata repositories and data catalogs to enable discovery, classification, and reuse of data assets; tag sensitive data and support data privacy and masking policies.
  • Implement data governance operating procedures for domain councils and steering committees, prepare agendas, facilitate workshops, and drive cross-functional decisions and approvals.
  • Design data migration and consolidation strategies for mergers, acquisitions, or system decommissions; lead complex data mapping, transformation, reconciliation, and cutover activities.
  • Translate complex technical designs into clear business-facing documentation and presentations, enabling non-technical stakeholders to understand data risks, value, and required investments.
  • Configure and extend MDM and data governance tooling to support business workflows, match/merge rules, survivorship logic, and user interfaces for stewardship and exception handling.
  • Build dashboards and reporting for data quality, stewardship activity, lineage coverage, and adoption metrics to monitor program health and drive continuous improvement.
  • Provide technical leadership during implementation: guide developers on best practices for data modeling, SQL performance, API design, and cloud data platform patterns (AWS/GCP/Azure).
  • Perform data risk and compliance assessments; recommend data retention, classification, and access control policies to support regulatory and internal audit requirements.
  • Estimate project scope, effort, and resource needs for data management initiatives; manage vendors and cross-functional teams to deliver on time and on budget.
  • Facilitate business capability workshops to capture domain rules, critical data attributes, and ownership, translating them into enforceable data standards and governance artifacts.
  • Mentor junior data professionals and steward communities; create training materials and run onboarding sessions for new governance processes and tools.
  • Manage stakeholder communications and change management, create the narrative for adoption, and align executive sponsors to secure sustained funding and attention for data programs.
  • Continuously evaluate emerging data management technologies and practices (graph databases, knowledge graphs, data contracts) and recommend pilot opportunities that can accelerate business value.

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.
  • Assist with documentation and training materials for end-users and stewards.
  • Perform periodic data stewardship audits and reconciliation checks for critical master data domains.
  • Validate design alternatives for scalability, performance, and maintainability in hybrid cloud environments.

Required Skills & Competencies

Hard Skills (Technical)

  • Data Governance: design and operationalize governance frameworks, policies, council structures, and stewardship models.
  • Master Data Management (MDM): hands-on experience implementing MDM solutions (Informatica MDM, Reltio, SAP MDG, Oracle) and configuring match/merge/survivorship logic.
  • Data Quality: proficiency with data quality tooling and techniques (profiling, matching, standardization, deduplication) and ability to define measurable DQ KPIs.
  • Data Modeling: strong conceptual, logical, and physical modeling skills, entity relationship modeling, and canonical model design.
  • SQL & Relational Databases: advanced SQL for profiling, reconciliation, ETL validation, and performance tuning.
  • ETL/ELT & Integration: experience with data integration patterns and tools (Informatica PowerCenter, Talend, SSIS, DBT, Apache Airflow) and APIs/streaming.
  • Metadata & Lineage Tools: experience implementing or integrating with data catalogs and metadata repositories (Collibra, Alation, Informatica EDC).
  • Cloud Data Platforms: familiarity with AWS/Azure/GCP data services (Redshift, Snowflake, BigQuery, Databricks) and cloud-native patterns for MDM and data orchestration.
  • Scripting & Automation: ability to use Python, Shell, or similar languages to automate profiling, validation, and integration tasks.
  • Data Privacy & Compliance: knowledge of GDPR, CCPA, HIPAA and practical experience implementing controls, classification and masking.
  • BI & Analytics Integration: understanding of downstream BI tools (Tableau, Power BI, Looker) and requirements for trusted data consumption.
  • Solution Design & Architecture: translate business requirements into scalable, secure, maintainable data solutions and reference architectures.
  • Vendor & Project Management: run vendor selection, POCs, and manage third-party partners during implementation and support phases.
  • DevOps/CI-CD for Data: understanding of versioning, deployment pipelines and testing practices for data pipelines and MDM configurations.

Soft Skills

  • Stakeholder Management: proven ability to engage executives and business owners, build consensus, and drive decisions across functions.
  • Communication: clear written and verbal skills to produce concise documentation, executive summaries, and training content.
  • Consulting Mindset: client-focused, outcome-oriented, comfortable delivering recommendations, trade-offs, and roadmaps.
  • Problem Solving: analytical thinker with a methodical approach to diagnosing root causes and designing pragmatic solutions.
  • Facilitation & Workshop Leadership: skilled at running cross-functional workshops, eliciting requirements, and building domain glossaries.
  • Change Management: experience leading adoption activities, training programs, and measurement of behavioral change.
  • Prioritization & Time Management: manage competing priorities across programs, ensuring the highest business-impact items are delivered.
  • Mentoring & Team Development: ability to coach junior team members and build sustainable internal capabilities.
  • Adaptability: flexible working style across hybrid teams, fast-changing technical stacks, and regulatory environments.
  • Attention to Detail: meticulous in data profiling, rule definition, and release validation to reduce production incidents.

Education & Experience

Educational Background

Minimum Education:

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

Preferred Education:

  • Master's degree in Information Systems, Data Management, Business Analytics, or MBA.
  • Professional certifications (CDMP, DGSP, TOGAF, Cloud certs, vendor MDM certifications).

Relevant Fields of Study:

  • Computer Science
  • Information Systems
  • Data Science
  • Business Administration
  • Statistics / Applied Mathematics

Experience Requirements

Typical Experience Range: 5 - 12 years in data management, data governance, or MDM roles; mid-to-senior level preferred.

Preferred:

  • 7+ years with direct experience leading MDM and governance implementations across multiple domains (customer, product, supplier).
  • Proven track record delivering data quality improvements and operationalizing stewardship at enterprise scale.
  • Experience working in regulated industries (finance, healthcare, telecommunications) and with cloud data platforms and modern data tooling.
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