Vice President, Data & Analytics

🔥 0 minutes ago

🏈 Ohio – Remote

🏈 Ohio – Remote

⏰ Full Time

🔴 Lead

📉 Data Analyst

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Hillenbrand

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

🍽️ Food & Beverage

💼 Consulting

📦 Logistics

Food & Beverage • Consulting • Logistics

Hillenbrand is a global provider of highly engineered, mission-critical processing equipment and systems, serving a diverse range of industries including durable plastics, food, and recycling. With a commitment to innovation and sustainability, Hillenbrand focuses on shaping solutions that impact lives and drive growth in a continually changing world. The company emphasizes excellence and continuous improvement, ensuring their products not only meet present-day needs but also anticipate future demands.

📋 Description

• Provide executive leadership for the organization’s data strategy, data governance, enterprise data warehouse, business intelligence, and AI initiatives • Set direction and remain hands-on in platform engineering alongside the team • Lead a small global team and establish the operating model, hiring plan, and delivery priorities • Partner with business and enterprise stakeholders to align data initiatives with organizational priorities • Establish enterprise data governance and stewardship, including data ownership, quality standards, and access policy • Manage vendor and platform costs, including compute governance and storage lifecycle policies • Engineer and govern lakehouse platforms, including Databricks, Delta Lake, SQL warehouses, workflows, and Unity Catalog • Design data architectures, dimensional models, multi-ERP integrations, and CDC/replication solutions • Lead platform assessment and rationalization, data-quality profiling, lineage reconstruction, and storage/compute cost reduction • Develop and implement continuous data-quality frameworks and financial reconciliation processes • Plan pragmatic migrations while keeping certified models and executive dashboards live • Define and drive AI/ML and generative-AI strategy and prioritize high-value use cases • Establish responsible-AI and model governance for predictive and generative systems • Enable self-service analytics and citizen development through governed data products and a trusted semantic layer • Report to the Chief Enterprise Business Services Officer and partner with indirect stakeholders across the business

🎯 Requirements

• Bachelor’s degree in Data Science, Information Systems, Computer Science, or related field, or equivalent experience • 10 or more years of progressive experience in analytics, business intelligence, and data administration • Expertise in data governance, data architecture, BI platforms, and cloud data technologies • Strong proficiency with data modeling and analytics methodologies • Strong executive communication and strategic planning skills • Demonstrated people-leadership, including building, mentoring, and retaining technical teams while remaining hands-on • Experience setting AI/ML and analytics strategy and establishing enterprise-scale data or AI governance • Expert-level Databricks or similar technology, including Delta Lake internals, SQL warehouses, and workflow/job orchestration • Deep experience with medallion architectures, efficient load design, ingestion deduplication, and grain/key discipline • Strong Unity Catalog governance skills, including access models, lineage, and system-table observability • Proven dimensional modeling expertise, including Kimball-style facts/dimensions, fact grain, conformed dimensions, and surrogate keys • Multi-ERP integration experience with SAP, Dynamics, Navision, JDE/E1, IFS, or similar • CDC/replication architecture experience • Experience leading platform assessment and rationalization, data-quality profiling, source-to-target lineage reconstruction, and cost reduction • Capability to establish automated data-quality tests, such as dbt tests or Delta Live Tables expectations • Experience reconciling warehouse facts to reported financials • Pragmatic migration-planning capability • Experience with responsible-AI and model governance, including evaluation, monitoring, privacy, and risk controls