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# Data Governance Architect

- **Company:** Wipro Limited
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Salary:** $80,000.0 - $158,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Data Governance, Metadata, Data Analytics
- **Published:** June 17, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=dae96f58ed827127

## About the Role

Do you have experience in Task prioritization?

## Description

The Data Governance Consultant is responsible for assessing, defining, and operationalizing enterprise data governance across multiple data domains. The role emphasizes governance frameworks, policies, operating models, and adoption-ensuring data is trusted, compliant, and consistently used across the organization., 1. Current State (As Is) Governance Assessment

 * Perform a comprehensive as is assessment of data governance capabilities, including:

o Data ownership, stewardship, and accountability models
o Business glossary, metadata, and lineage practices
o Data quality management approaches
o Privacy, security, and retention controls

 * Assess maturity by comparing current practices against:

o Industry best practices
o Recognized governance frameworks (e.g., DAMA, federated governance models)
o Regulatory expectations relevant to the organization

 * Identify gaps in governance coverage, consistency, and execution.

 3. Governance Framework & Best Practice Recommendations
 * Define and recommend a future state governance framework, including:

o Governance operating model (central, federated, or hybrid)
o Clear roles, RACI, and stewardship responsibilities
o Standards for data definitions, quality, and lifecycle management

 * Propose best practice governance processes based on prior enterprise implementations, tailored to organizational culture and maturity.

 4. Governance Technology Enablement
 * Advise on the selection and use of data governance and catalog platforms (e.g., business glossary, metadata, lineage, policy management).
 * Define how governance processes and policies should be operationalized through tools and workflows.
 * Ensure governance is embedded into day to day data and analytics activities.

 5. Roadmap, Prioritization & Change Enablement
 * Drive the development of a long term data governance roadmap, detailing:

o Target governance capabilities and maturity milestones
o Prioritized initiatives with sequencing and dependencies
o Quick win vs foundational improvements

 * Support change management and adoption by:

o Defining rollout and enablement strategies
o Aligning governance with business value and regulatory outcomes

Expected Outcomes

 * Clear understanding of current governance maturity and gaps
 * Pragmatic, business aligned governance framework
 * Improved trust, consistency, and compliance across data domains
 * Scalable governance model that supports analytics and AI adoption


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