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Disabled, Not available For bulk actions Supply Chain Data Governance

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Onsite

Disabled, Not available For bulk actions Supply Chain Data Governance

Saipsit

Disabled, Not available For bulk actions Supply Chain Data Governance

Skills

Product ManagementData AnalysisAISupply ChainComplianceRegulatory ComplianceRisk Management

2 months ago

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Important information


Contract type:

Permanent

Salary:

₹1,200,000 – ₹1,600,000 / year

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

11 August 2026

What they need


Position Summary:

The Supply Chain Data Governance Specialist plays a critical role in ensuring the accuracy, integrity, consistency, and strategic value of Supply Chain data. This role serves as a key connector between business and technical teams, operationalizing the organizations data governance framework to enable improved decisionmaking, cost optimization, operational efficiency, risk mitigation, and regulatory compliance. The Data Governance Specialist supports the design, implementation, and continuous improvement of data governance capabilities across Supply Chain data domains, with a strong focus on data quality management, metadata and lineage, stewardship enablement, policy application, and data issue identification and resolution.

This position is aligned with the Discipline Management organization and supports the objectives of the Product Management team by ensuring effective execution of data governance deliverables. The role reports to the Data Discipline Supervisor and works closely with data owners, data stewards, product teams, and technology partners across the enterprise.

Key Responsibilities

Execute and support the Data Governance Program across Supply Chain data domains in partnership with Data Owners, Data Stewards, and crossfunctional teams

Implement, maintain, and operationalize data governance policies, standards, and procedures

Support the definition, documentation, and maintenance of critical data elements and domainspecific data assets

Manage metadata, business glossaries, and data lineage within enterprise data governance tools (e.g., Collibra)

Define, steward, and enforce data quality rules; identify, analyze, and support resolution of data issues impacting operations and reporting

Track, triage, and report data issues and risks, partnering with technical and business teams to drive timely resolution

Participate in data governance council and working group meetings, presenting findings, risks, and improvement recommendations

Develop and support Supply Chain data literacy and stewardship enablement efforts

Define, develop, and monitor metrics and dashboards to track data quality, governance adoption, and improvement opportunities

Contribute to continuous improvement of governance processes, tools, and operating models

Required Qualifications:

Proven experience supporting the design and implementation of data governance frameworks, policies, standards, and operating models within large, complex organizations

Strong knowledge of data governance best practices and frameworks (e.g., DAMADMBOK, DCAM)

Handson experience with data quality management, metadata management, data lineage, and master/reference data concepts

Experience using data governance and metadata management tools such as Collibra

Solid understanding of data architecture, data models, BI platforms, and integration with analytics or AI initiatives

Demonstrated ability to collaborate effectively with both business and technical stakeholders

Preferred Qualifications:

Experience supporting Supply Chain, Operations, or data domains within assetintensive or industrial environments

Experience in the energy industry or similarly regulated environments

Ability to assess data governance maturity and contribute to roadmaps for improvement and value realization

Strong communication and stakeholder management skills, with the ability to influence and gain buyin across functions

What Success Looks Like in This Role:

Improved data quality, consistency, and usability across Supply Chain domains

Wellmaintained metadata, business definitions, and lineage supporting analytics and decisionmaking

Active and effective data stewardship engagement

Reduced data issues impacting operational and reporting outcomes

Increased adoption of data governance practices and data literacy across the organization

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