Director, Data Engineering & Analytics

KeHE Distributors, LLC•Naperville, IL

About The Position

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.

Requirements

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 lakehouses, 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, Microsoft Fabric, Azure, Snowflake, Redshift, Databricks, or equivalent platforms.
Ability to connect technical delivery to business outcomes, adoption, ROI, risk reduction, operational efficiency, and executive decision-making.
Strong knowledge of data governance, data security, access management, privacy, compliance, auditability, and production support expectations.
Experience establishing KPIs, service levels, delivery metrics, platform health measures, and continuous improvement routines.
Strong vendor management, budgeting, capacity planning, roadmap planning, and prioritization capabilities.
Exceptional written, verbal, and presentation skills, with the ability to communicate complex data and technology concepts to executive, business, and technical audiences.
Strong storytelling skills to translate analytics insights, platform investments, risks, decisions, and tradeoffs into clear leadership-level narratives.
Strategic thinking, critical problem-solving, and pragmatic execution skills with an entrepreneurial and future-looking mindset.
Strong relationship management skills and the ability to build trust across business, technology, security, architecture, and operations teams.
Ability to lead through ambiguity, manage competing priorities, influence without direct authority, and build scalable operating models.
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Analytics, Engineering, Mathematics, or a related technical field.
10+ years of progressive experience in data engineering, analytics, data architecture, and enterprise technology delivery.
5 to 7 years of people leadership experience managing managers, technical leads, data engineers, BI developers, analytics professionals, administrators, contractors, or offshore teams.
Demonstrated experience delivering enterprise data platforms, analytics products, reporting solutions, data pipelines, and governed self-service BI capabilities using agile, product-centric, or hybrid delivery methods.
Experience with DevOps or DataOps practices, including CI/CD, release management, automated testing, monitoring, incident management, documentation, and operational support.
Experience with cloud-based providers and enterprise data services, preferably AWS and/or Microsoft data platforms.
Experience with modern integration and analytics technologies such as SQL, Python, APIs, orchestration tools, Power BI, semantic models, ETL/ELT tools, data catalogs, Redshift, Fabric, Snowflake, Databricks, or equivalent platforms.
Experience leading cross-functional analytics initiatives that serve business functions such as Finance, Commercial, Operations, Supply Chain, or Enterprise IT.
Experience with budgeting, vendor management, consulting partner oversight, delivery governance, and executive stakeholder communication.

Nice To Haves

A Master’s degree is preferred.

Responsibilities

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.