Data Governance Consultant

Data Governance Consultant

Experience: 8–12+ Year

About the Role

The Data Governance Consultant is the organizational design and regulatory compliance specialist within Bristlecone's SC Data & AI practice. This role owns the governance model and policy deliverables within SC Data Strategy engagements, designs the data stewardship program for MDM implementations, and leads SC regulatory data assessments under for CSRD, EUDR, UFLPA, and CBAM exposure. This consultant will ensure that the data Bristlecone builds for clients is governed, auditable, and fit for AI consumption — not just reporting.

What You'll Do

• Design SC data governance frameworks and operating models — defining Domain Owner, Data Steward, and Data Custodian roles across demand, supply, inventory, logistics, and sourcing master data domains
• AI governance: Extend governance models to cover AI-specific requirements — data lineage for AI model inputs, data quality SLAs for feature stores, bias monitoring for SC AI models, and audit trails for Agentic AI decisions
• Deliver the governance model component of SC Data Strategy engagements — producing the SC Data Governance Council charter, data stewardship organization design, data policies, and a 90-day activation plan
• Lead data stewardship program design for MDM and Data Quality engagements — steward onboarding, DQ rule training, escalation workflow design and stakeholder management
• Regulatory AI intersection: Conduct SC regulatory data assessments
• Facilitate cross-functional alignment between various LoBs on SC data ownership
• Draft reusable Bristlecone IP: SC data policy templates, AI governance frameworks for SC, governance council charter standards, and regulatory data mapping methodologies

What You'll Bring

• 6+ years in data governance, data management, MDM, or regulatory compliance — with meaningful exposure to supply chain, manufacturing, CPG, or life sciences industries
• Working knowledge of data governance frameworks — DAMA-DMBOK, DCAM, or equivalent — able to adapt frameworks to SC domain realities and AI-era requirements rather than applying generic templates
• AI governance awareness: Familiarity with AI governance concepts: model governance, data lineage for ML, feature store data quality, responsible AI principles — able to extend traditional data governance to cover AI system inputs and outputs
• Knowledge of SC regulatory requirements across at least two of: CSRD (Scope 3 emissions), EUDR (commodity traceability), UFLPA (supply chain audits), or CBAM (embedded carbon data)
• Demonstrated experience designing stewardship programs with evidence of sustained adoption
• Strong cross-functional facilitation skills — able to run workshops involving CXOs

Bonus If You Have

• CDMP (Certified Data Management Professional) or equivalent data governance certification
• Hands-on experience with data governance or catalog tools: Collibra, Alation, Microsoft Purview, Ataccama ONE, or Informatica Axon
• SC domain practitioner background — understanding SC business processes from the inside, which determines whether governance models are practical or just theoretically correct
• ESG or sustainability data management experience: GHG Protocol, CSRD ESRS standards, CDP reporting, or familiarity with how AI tools (e.g. AI-estimated emissions) are being assessed for regulatory acceptability under CSRD