Senior Consultant, Analytics Governance
Cargill is committed to providing food and agricultural solutions to nourish the world in a safe, responsible, and sustainable way. Sitting at the heart of the supply chain, we partner with farmers and customers to source, make and deliver products that are vital for living.
Our 155,000 team members innovate with purpose, providing customers with life’s essentials so businesses can grow, communities prosper, and consumers live well. With over 160 years of experience as a family company, we look ahead while remaining true to our values. We put people first. We reach higher. We do the right thing—today and for generations to come.
Job Purpose and Impact
The Senior Consultant, Analytics Governance is responsible for designing, operationalizing, and scaling governance guardrails across the analytics ecosystem. This role ensures trusted, reusable, discoverable, and well-managed analytics assets, including semantic models, data products, reports, dashboards, and GenAI-enabled analytics across a federated enterprise environment.The role partners closely with Data Engineering, Data & Analytics teams, Product Owners, Platform teams, and Risk/Compliance stakeholders to embed governance into the analytics lifecycle. The objective is to grow enterprise trust in analytics, increase reuse of certified assets, streamline lifecycle management, and reduce time to insights.This position requires strong influence skills, deep knowledge of modern BI ecosystems (e.g., Power BI), metadata strategy, and experience governing both traditional analytics and emerging GenAI-enabled use cases.
Key Accountabilities
Analytics Guardrails & Governance: Define and evolve governance standards for semantic models, data products, dashboards, reports, and workspaces. Establish certification, endorsement, quality, testing, versioning, documentation, and lifecycle policies that balance control with agility.
Certification & Reusability: Lead the certification framework for semantic models, curated datasets, and enterprise reports. Set criteria for trusted assets, drive reuse to reduce duplication, and improve discoverability of standardized metrics.
Metadata Strategy: Partner with Data Engineering to unify business and technical metadata. Define standards for definitions, lineage, ownership, stewardship, and data classification. Ensure metadata supports discoverability, compliance, and alignment across the semantic layer and reporting tools.
GenAI Analytics Governance: Create guardrails for GenAI-enabled analytics and self-service AI, ensuring alignment with data classification and access controls.
Power BI Workspace Governance:Define workspace structures, access roles, lifecycle rules, archival processes, and usage monitoring. Promote semantic model best practices to reduce duplication and improve report discoverability.
Lifecycle & Asset Management: Establish end-to-end governance for analytics assets—from intake and build, through certification and promotion, to monitoring and retirement. Implement clear ownership and scalable processes.
Stakeholder Engagement & Change Enablement: Advise creators, leaders, and technical teams. Provide training and office hours to foster adoption of governed, reusable analytics. Measure impact through KPIs such as reuse, certification rates, and reduced duplication.
Qualifications
- Minimum requirement of 4 years of relevant work experience. Typically reflects 5 years or more of relevant experience.
- Strong experience with Power BI (semantic models, workspaces, deployment pipelines, governance practices).
- Experience designing or operationalizing analytics governance frameworks.
- Experience working in a federated analytics or data organization.
- Demonstrated experience influencing cross-functional stakeholders without direct authority.
Preferred Experience
- 7+ years in analytics, BI, data governance, or related field.
- Experience with enterprise data catalogs and metadata management tools.
- Experience governing semantic layers and enterprise metrics.
- Exposure to GenAI, AI governance, or responsible AI frameworks.
- Familiarity with data classification standards and regulatory requirements.
- Experience supporting self-service analytics at scale.
Compensation Data
The expected salary for this position is $105,000 - $160,000. Compensation varies depending on a wide array of factors including but not limited to the specific location, certifications, education, and level of experience. The disclosed range estimate may be adjusted for any applicable geographic differential associated with the location at which the position may be filled. This position is eligible for a discretionary incentive award. The incentive award amount is dependent upon company performance and your personal performance. At Cargill we put people first. As part of your overall rewards, we offer a comprehensive benefit program including medical and/or other benefits dependent on the position offered and hours worked. Visit: https://www.cargill.com/page/my-health/mh-health-and-wellness to learn more (subject to certain collective bargaining agreements for Union positions).
Equal Opportunity Employer, including Disability/Vet.
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