Head of Data Strategy & Enablement

Job Title Head of Data Strategy & Engineering Location Chicago (Hybrid) On-site cadence flexible; occasional travel to collaborate with partner teams and operating units.

About The Company A U.S.-based private equity firm focused on partnering with lower middle-market industrial growth businesses. Founded in the 2010s, the firm invests in high-performing companies with differentiated value propositions that could benefit from operational, technology, and strategic resources to scale, optimize, and thrive.

The portfolio companies span essential industrial sectors, creating opportunities to apply shared data/technology patterns and compound impact to drive enterprise value. Technology is treated as a purposeful growth lever. The firm is intentionally elevating data and technology to improve commercial and operational performance, enable cross-company collaboration, and build scalable analytics/automation capabilities both at the fund level and within the portfolio companies.

This is an Executive Opportunity, seeking a Principal Engineer to serve as both a Practitioner and Executive Technologist to build a foundation for growth and own the company roadmap for data, AI, and technology value creation.

Job Summary Own the enterprise data strategy and build the modern data platform. Define the roadmap, standardize data across entities, integrate key systems via APIs, and enable high-quality analytics that leadership and operators can use to drive enterprise value. You’ll start as a hands-on builder and evolve into the executive owner of data and technology capabilities.

The vision is to build a Data Mart on structured and unstructured data enabling the firm to deliver not just valuable insights but also create efficiency and effectiveness across each portfolio company. This will enable the operators of each business and the fund manager to have the next best action approach. Looking for a best-in-class business athlete with great executive function and communication skills. Must understand finance and an MBA and/or Private Equity experience is preferred but not required.

Key Responsibilities

• Set the vision & roadmap: Translate business goals into a pragmatic, phased data strategy and operating model across ingestion, modeling, governance, and analytics.
• Build the platform: Lead architecture and implementation in a Microsoft Fabric Azure environment using a medallion approach (bronze/silver/gold) with strong standards and documentation.
• Integrate critical systems: Design and manage APIs to ERP/CRM/HRIS and subscription data sources; ensure scalable, reliable pipelines into the lakehouse.
• Enable the business: Partner with internal “customers of the data” to prioritize use cases, deliver self-service analytics (Power BI), and raise data fluency enterprise-wide.
• Stabilize & standardize: Bring order to the environment—data quality, lineage, semantic models, and access patterns that make insights fast and trustworthy.
• Orchestrate partners & resources: Coordinate with existing consulting partners; plan the evolution of internal resourcing (e.g., hiring a data engineering IC) and leverage cross-functional analysts as needed.
• Measure value: Define KPIs for platform reliability, time-to-insight, stakeholder adoption, and business outcomes; iterate the roadmap accordingly.

Requirements (Must-Haves)

• 8 years building/owning modern data platforms with increasing leadership scope; comfortable operating as the hands-on owner in an ambiguous, multi-entity environment.
• Deep experience with Microsoft Fabric and Azure services; strong grasp of medallion/lakehouse patterns and semantic modeling.
• Proven integration of APIs from core business systems (ERP/CRM/HRIS) and third-party data providers; pipeline orchestration and reliability at scale.
• Proficiency with Power BI and enablement of self-service analytics for non-technical stakeholders.
• Excellent stakeholder management and communication; able to partner with senior leaders and cross-functional teams as the “translator” between business needs and technical execution.
• Solid business acumen—especially comfort with accounting/finance fundamentals and how operational data maps to financial “score-keeping.”

Nice to Haves

• Experience standing up a small data engineering team and establishing data governance/operating mechanisms in federated organizations.
• Familiarity with subscription data (e.g., market/financial datasets) and harmonizing them with internal sources.
• Exposure to Copilot/GenAI concepts for productivity/insight acceleration; readiness to evaluate advanced analytics as the foundation matures.

BenefitsCompetitive compensation with performance incentives; comprehensive health & retirement programs; generous PTO; professional development support; and flexibility in shaping the team and technology choices as the function grows.