OverviewThe Director of Data defines Kemin’s enterprise data strategy and provides architectural direction, standards, and prioritization to enable analytics, business intelligence, and AI initiatives. Operating within a hybrid model, this role sets enterprise data architecture expectations and governance while closely partnering with IT teams responsible for execution and platform operations. The Director of Data aligns data priorities with business, Operations, R&D, Finance, etc. needs, restores trust in enterprise data, and ensures data investments translate into measurable business value.
Responsibilities
Enterprise Data Strategy & Direction
- Establish the enterprise data strategy and targetstate architecture that supports analytics, AI, and decisionmaking use cases.
- Translate business, Operations, Finance, R&D, etc. priorities into clear data architecture and sequencing guidance.
- Define what "analytics-ready" and 7AI-ready8 data means at Kemin and ensure alignment across teams.
Data Standards & Oversight
- Define and maintain data standards, patterns, and design principles for structured and unstructured data.
- Provide functional leadership and architectural direction to data architecture resources operating within IT.
- Chair or cochair architecture governance forums to review designs, resolve tradeoffs, and approve exceptions.
Data Governance, Quality & Trust Enablement
- Define governance frameworks, roles, and accountability models aligned to highvalue data domains.
- Set data quality thresholds and improvement priorities based on analytics and AI business needs.
- Partner with IT and business data owners to remediate critical data quality issues and improve usability.
Data Analytics and Data Engineering
- Define platform expectations and workload strategies (e.g., Databricks, Fabric) to support analytics and AI use cases.
- Partner with IT to ensure platform decisions are aligned to data strategy rather than infrastructure convenience alone.
- Ensure priority AI pilots and analytics initiatives are supported by appropriate data foundations and pipelines.
Cross Functional Leadership & Development
- Partner with Finance to define ROI measurement frameworks and baseline metrics for data and AI investments.
- Align stakeholders on priorities, trade offs, and sequencing when data quality or architecture constraints exist.
- Communicate data strategy, progress, and risks clearly to senior leadership in business terms.
Qualifications
- Education and Experience:
- Bachelors Degree in Data Science, Computer Science, or Analytics with 10+ years of related experience.
- Strong executive communication skills; able to translate data strategy into business outcomes for non-technical leadership.
- Background in manufacturing, life sciences, chemicals, CPG, or other R&D-intensive, data-complex environments.
- Demonstrated success improving data quality, trust, and usability across fragmented systems and legacy platforms.
- Experience partnering with IT architecture and engineering teams while setting enterprise data standards, priorities, and design expectations.
- Strong understanding of modern data platforms (e.g., lakehouse architectures) and their role in enabling analytics and AI.
- Proven ability to influence senior stakeholders and drive alignment without direct authority.
- Experience establishing or scaling data governance frameworks, stewardship models, or domain ownership structures.
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