Director, Data Engineering & Architecture

Responsibilities

• Define and execute the enterprise data engineering strategy supporting business growth, operational excellence, analytics, and AI initiatives.
• Establish enterprise standards for data ingestion, integration, transformation, storage, quality, and delivery.
• Create a scalable data architecture capable of supporting a rapidly growing and acquisition-driven organization.
• Create a multi-year roadmap for enterprise data capabilities and platform investments.
• Ensure data architecture decisions align with broader Digital & AI, IT, and business strategies.
• Lead the design, implementation, and operation of the company’s enterprise data platform and lakehouse architecture.
• Oversee enterprise data storage, metadata management, lineage, access management, and audit capabilities.
• Define architectural standards that promote reliability, performance, scalability, and maintainability.
• Evaluate and recommend emerging technologies that enhance the company’s data capabilities.
• Establish and maintain enterprise data domains, business entities, and authoritative sources of truth.
• Lead development of enterprise information architecture frameworks that support analytics, reporting, and AI solutions.
• Oversee master data management strategies for critical business entities, including clients, projects, employees, vendors, and financial data.
• Ensure consistency of data definitions, business rules, and enterprise reporting standards.
• Partner with Data & Information Architects to maintain enterprise data models and architecture standards.
• Develop repeatable integration frameworks for newly acquired firms and business units.
• Assess data quality, system architecture, and integration complexity during acquisition activities.
• Create data onboarding playbooks that accelerate integration timelines while maintaining quality and governance standards.
• Partner with business leaders to prioritize enterprise integration efforts based on strategic value and business impact.
• Drive consolidation of fragmented systems and data assets into enterprise platforms where appropriate.
• Partner with the Director of Data & AI Governance to operationalize governance controls within enterprise platforms and workflows.
• Ensure technical implementation of classification, retention, lineage, stewardship, and access management requirements.
• Establish data quality frameworks, monitoring capabilities, and remediation processes.
• Support audit readiness and compliance requirements through robust technical controls and documentation.
• Promote enterprise accountability for data ownership and stewardship.
• Recruit, develop, and lead a high-performing team of Data Engineers, Data & Information Architects, and Governance professionals.
• Establish clear performance expectations, development plans, and career pathways.
• Foster a culture of collaboration, innovation, accountability, and continuous improvement.
• Mentor team members and encourage adoption of best practices across the organization.
• Build organizational capability through knowledge sharing, training, and partnership.
• Serve as a trusted advisor to executive leadership on enterprise data strategy and capabilities.
• Partner with Finance, Operations, Human Resources, Technology, and Business Unit leaders to understand priorities and align solutions.
• Collaborate closely with AI, Automation, and Analytics leaders to ensure data platforms support future use cases.
• Communicate technical concepts effectively to both technical and non-technical audiences.
• Translate business objectives into scalable data solutions that deliver measurable value.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Data Science, Engineering, or a related discipline.
• 12+ years of progressive experience in data engineering, data architecture, or enterprise data management.
• 5+ years of leadership experience managing technical teams and enterprise-scale initiatives.
• Demonstrated success designing and implementing modern enterprise data platforms.
• Experience integrating multiple enterprise systems and data sources within complex organizations.
• Strong understanding of: Data architecture, data engineering, master data management, information architecture, data governance, data quality management.
• Experience building enterprise reporting, analytics, and data product capabilities.
• Strong business acumen and ability to align technical investments with organizational objectives.
• Exceptional communication, collaboration, and stakeholder management skills.