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Director, Data Engineering 

The Director of Data Engineering is a key senior leader responsible for the strategy, architecture, and execution of the enterprise data engineering function. This leader will build and scale a high-performing team, drive strategy and design of the data engineering framework for reporting needs, facilitates strategy around the data warehouse, partners with other IT leaders to provide availability of data for AI/ML initiatives, assists with business intelligence, and core operational systems for seamless reporting. Reporting to senior technology leadership, this role serves as a strategic partner to IT, Analytics, and business stakeholders to ensure data is reliable, governed [in partnership with master data management], and accessible at scale.

This is a high-impact opportunity for a technically grounded, people-first leader who thrives in a fast-paced environment and is energized by building scalable systems during a period of significant growth, including M&A integration and cloud transformation.

Responsibilities:

• Leadership & Strategy
  • Define and drive the enterprise data engineering roadmap, aligned to business and technology goals
  • Build, lead, and mentor a multi-disciplinary team of data engineers (10-15) and product owner(s) (1-2)
  • Partner with the CIO, Analytics, AI, and business leadership to prioritize and deliver data capabilities
  • Establish engineering standards, best practices, and an operational excellence framework across the data organization
  • Champion a culture of data quality, engineering rigor, and continuous improvement
• Platform & Architecture
  • Architect and oversee scalable data pipelines, data lakes, warehouses, and real-time streaming infrastructure
  • Lead cloud-native data platform strategy and adoption across Azure, AWS, or GCP environments
  • Own the selection, implementation, and lifecycle management of data engineering tools and platforms
  • Ensure data platform reliability, performance, and cost efficiency at scale
  • Partner with Platform Development Architects and leadership on integration patterns across key enterprise systems, including ERP, ServiceNow, and supply chain platforms
• Data Governance & Quality
  • Own and evolve the enterprise data governance framework, including data lineage, cataloging, and access controls
  • Define and enforce data quality standards, measurement, and remediation processes
  • Partner with Security and Legal to ensure compliance with data privacy regulations and policies
  • In partnership with the Director of Development and AI, drive adoption of clean, governed, AI-ready data as a core organizational asset.
• Delivery & Operations
  • Manage team delivery across multiple concurrent programs, including integration workstreams from M&A activity
  • Lead data engineering support for AI/ML platform enablement 
  • Oversee vendor relationships, contracts, and budget for data infrastructure and tooling
  • Establish SLAs, incident management, and monitoring for data platform operations

Basic Qualifications:

• 10+ years of progressive experience in data engineering, data architecture, or a related technical discipline
• 5+ years of people leadership experience, including managing and developing senior engineers and managers; Communication is a critical facet for this role with an ability to manage up, to the side or down.
• Proven track record of architecting and delivering enterprise-scale data platforms in production
• Deep expertise in modern data stack tooling (e.g., Azure SQL, Azure Fabric, Kafka, Snowflake, Databricks, or equivalents)
• Strong cloud data platform experience on Azure, AWS, or GCP
• Demonstrated experience in data governance programs and data quality frameworks
• Ability to translate complex business requirements into pragmatic technical strategy and roadmaps
• Strong executive communication skills; comfortable presenting to C-suite and board-level audiences
• Experience operating in dynamic, growth-stage environments, including M&A integration preferred
• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field; Master’s preferred

Preferred Qualifications:

• Experience in IT services, managed services, or enterprise technology industries
• Familiarity with ERP, ServiceNow, or supply chain data ecosystems
• Experience leading data strategy and integration through M&A events
• Exposure to data mesh, data product, or federated governance models
• Relevant certifications in cloud data platforms (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate)
• A strategic mindset paired with a bias for action and hands-on delivery
• Passion for building reliable, scalable, and well-governed data systems
• A collaborative and inclusive leadership style with the ability to influence across levels
• Intellectual curiosity and a continuous improvement mindset
• High standards for data quality and a commitment to engineering excellence

Travel: 

• 15%