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We are looking for an experienced Data Governance Consultant to join the Data & Analytics consulting practice, delivering data governance advisory and data catalog implementation engagements for clients. This is a client-facing role that requires a strong understanding of data governance principles, metadata management, data catalog implementation, and stakeholder engagement.
The role requires someone who can balance governance advisory work with hands-on catalog enablement, adoption, and continuous improvement.
Key Responsibilities
Support the development and maintenance of the client’s data governance framework, including standards, policies, procedures, data quality rules, and stewardship guidelines.
Run or support data maturity assessments and act as a bridge between the engagement team and client business and technology stakeholders to identify gaps, define remediation plans, and drive adoption of governance requirements.
Lead or significantly contribute to the implementation and adoption of the client’s data catalog platform (e.g., OpenMetadata, Collibra, Alation, Informatica, or similar), including metadata onboarding of priority source systems and validation of cataloged assets.
Set up and maintain data domains, ownership, stewardship workflows, business glossary terms, and classifications in the catalog, and establish practical approaches for capturing lineage, usage, and data quality across priority assets.
Translate governance policies and standards into executable workflows, SOPs, and operating processes within the catalog, and track governance and catalog KPIs such as metadata coverage, glossary completeness, stewardship participation, and adoption progress.
Prepare clear documentation, status updates, and executive-level communication for client and internal stakeholders, and provide day-to-day technical guidance to junior consultants on the engagement.
What We’re Looking For
5–10 years of experience in data governance, metadata management, data management, consulting, or related roles, preferably in financial services, banking, or enterprise data environments.
Strong understanding of data governance principles, frameworks, and best practices such as DAMA-DMBOK, DCAM, data stewardship, metadata management, data quality, and data ownership.
tewardship, metadata management, data quality, and data ownership.
Work arrangement
No
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