Director, Data Engineering & Analytics

Naturally Network is an agent of change.

• Pay Range: $/Yr.
  
  - $/Yr.
• Shift Days: , Shift Time:
• Benefits on Day 1
  • Health/Rx
  • Dental
  • Vision
  • Flexible and health spending accounts (FSA/HSA)
  • Supplemental life insurance
  • 401(k)
  • Paid time off
  • Paid sick time
  • Short term & long term disability coverage (STD/LTD)
  • Employee stock ownership (ESOP)
  • Holiday pay for company designated holidays

At KeHE, we're obsessed with creating solutions, unboxing potential, and serving others - and it all starts with you. As an employee-owned distributor of natural and organic, specialty, and fresh products, we're committed to making a positive impact and scaling our success together. With a culture that fosters development and opportunity, you'll be embarking on a career that's moving forward. When you join KeHE, you're becoming part of a team that is a force for good.

The Director, Data Engineering & Analytics is accountable for the strategy, delivery, reliability, and continuous improvement of KeHE's enterprise data, analytics, and business intelligence capabilities. This leader directly manages and mentors managers and senior professionals responsible for data engineering, analytics platforms, semantic models, reporting solutions, data governance, and operational support. The role partners closely with business and technology leaders to translate enterprise priorities into scalable data products, actionable insights, and measurable business outcomes while ensuring solutions align with KeHE's architecture principles, security standards, and Mission, Vision, and Values.

• Provide strategic, technical, and operational leadership across data engineering and analytics platform teams.
• Own and communicate the data and analytics roadmap in partnership with Product Management, business stakeholders, enterprise architecture, security, and infrastructure teams.
• Lead the design, build, deployment, and support of scalable data pipelines, curated data products, reporting solutions, semantic layers, and analytics platforms.
• Drive modernization of enterprise analytics capabilities, including cloud data platforms, Power BI, data lakehouse or warehouse patterns, orchestration, automation, metadata management, and self-service analytics enablement.
• Establish and monitor delivery, quality, adoption, reliability, and operational health metrics for data products, platforms, and team performance.
• Ensure data solutions follow architecture principles, information security requirements, privacy expectations, data governance standards, and change management practices.
• Partner with business leaders across Finance, Commercial, Operations, Supply Chain, and IT to prioritize high-value analytics use cases and deliver measurable outcomes.
• Champion data quality, master data alignment, lineage, stewardship, access controls, documentation, and sustainable support models.
• Lead teams through product-centric delivery practices, including requirements refinement, design reviews, development, testing, release readiness, validation, adoption support, and continuous improvement.
• Manage budgets, vendor and consulting partner relationships, resource plans, work plans, schedules, risks, and performance expectations.
• Hire, coach, mentor, and develop managers and individual contributors; create individual development plans, succession plans, and clear team goals.
• Foster a culture of innovation, accountability, proactive communication, continuous learning, automation, and cross-functional collaboration.
• Stay current with emerging data, analytics, AI, cloud, governance, and integration trends and apply them pragmatically to improve business outcomes.
• The above statement of duties is not intended to be all inclusive, and other duties will be assigned as needed.

• Proven track record leading data engineering, analytics, BI, or data platform teams in a matrixed enterprise environment.
• Strong understanding of modern data architecture patterns, including cloud data platforms, data warehouses, data lakes or lake houses, ETL/ELT, orchestration, semantic modeling, APIs, and governed self-service analytics.
• Deep experience with SQL, dimensional modeling, data integration, data quality practices, metadata, lineage, and enterprise reporting design.
• Experience with BI and analytics platforms such as Power BI and with cloud-based data services, preferably AWS,…