Director Data Engineering

Responsibilities

• Team Leadership and Organizational Development (25%)
  • Build, lead, and develop the data engineering team, including hiring, coaching, performance management, and career development.
  • Establish team structure, roles, and staffing plans (including contractor-to-FTE conversion), and cultivate a high-performing, accountable engineering culture.
  • Set objectives, allocate work, and ensure the team consistently delivers against commitments.
• Data Engineering Strategy and Delivery (25%)
  • Own the strategy, roadmap, and delivery of the enterprise data platform on Databricks and AWS, including the Medallion model (Landing, Bronze Raw, Silver Standardized, Gold Consumption/Aggregates/Semantic).
  • Prioritize the portfolio of data initiatives, manage delivery timelines and dependencies, and hold the team accountable for reliable, on-time execution that anticipates future analytics, GenAI, and agentic AI workloads.
• Platform Operations, Reliability, and Governance (20%)
  • Ensure the production data platform is reliable, secure, and cost-efficient, with clear SLAs, monitoring, and incident management.
  • Oversee the governance model, including Unity Catalog administration, RBAC, data classification, lineage, and quality, ensuring compliance with SOX, PCI-DSS, and other regulatory obligations in partnership with the Data Governance Council and security leadership.
• Budget, Vendor, and Stakeholder Management (15%)
  • Own the data engineering budget, including cloud spend, tooling, and consulting partners.
  • Lead vendor evaluation, selection, and management, and make build-vs-buy and platform investment decisions.
  • Partner with functional executives to align the roadmap to business priorities, and present strategy, progress, risks, and investment recommendations to senior and executive leadership.
• Technical Direction and Standards (15%)
  • Set the engineering standards, reference architectures, and best practices the team follows, including Infrastructure-as-Code (Terraform), monorepo CI/CD (GitLab), and pipeline design patterns (PySpark, Delta).
  • Provide senior technical direction and design review, guiding the Data Architect and engineers and serving as an escalation point for the hardest technical problems.
  • Sponsor enterprise master data management (MDM), including the Unique Customer ID (UCID) program. Ensure the data platform and migration strategy support the future Acumatica ERP implementation.
  • Champion the company's AI enablement agenda, including reusable data/AI platform capabilities and AI Office Hours.
  • Contribute to workforce planning, headcount business cases, and organizational design for the broader Business Technology and Data function.

Qualifications

• Strong technical foundation in SQL, Python, PySpark, data modeling, CI/CD, and Infrastructure-as-Code, sufficient to lead architecture decisions and earn the trust of a senior engineering team.
• Demonstrated ability to hire, develop, and retain top engineering talent and build a high performing team culture.
• Excellent leadership, communication, and influence skills, with a proven track record aligning engineers, executives, and cross-functional partners.
• Sound business judgment on budget, vendor, and build-vs-buy decisions.
• 12+ years of progressive experience in data engineering, data platform, or data architecture roles.
• 4+ years of experience directly managing and building engineering teams, including hiring and performance management.
• 5+ years of hands-on experience with Databricks (Lakehouse architecture, Delta Lake, Unity Catalog) and AWS at enterprise scale.
• Demonstrated ownership of platform delivery and operations in a regulated environment (SOX, PCI-DSS, or similar).
• Proven experience owning a budget and managing vendor/consulting partner relationships.