Senior Director of Enterprise Data

Join our team as the Senior Director of Enterprise Data, where you will lead the transformation and maturity of our data ecosystem. You will own the end-to-end data strategy, evolve our data platform architecture, and institutionalize federated data governance. This role requires a proven track record in data engineering, architecture, and enterprise data management, as well as strong leadership and change management skills.

• Architect the Future: Design, execute, and evolve a scalable data platform roadmap capable of handling a multi-billion dollar enterprise’s volume, velocity, and variety of data.
• De-bottleneck Legacy Infrastructure: Transition our centralized pipelines into a modern, decoupled data architecture.
• Data as a Product: Implement a "Data as a Product" mindset across engineering teams, ensuring datasets have strict Service Level Objectives (SLOs), rigorous uptime, and high catalog discoverability.

• Proven Scale Experience: Minimum of 12+ years of progressive leadership in data engineering, data architecture, or enterprise data management, with explicit experience inside an organization operating in a B2B environment at a $1B to $5B+ revenue scale
• Business Acumen: Ability to translate complex technical jargon into clear business value, financial ROI, and strategic alignment for C-suite executives
• Architectural Fluency: Deep hands-on and strategic familiarity with modern cloud data stacks (e.g., Snowflake, Databricks, BigQuery, AWS/Azure data suites) and enterprise MDM platforms (e.g., Informatica, Reltio, Semarchy, Profisee)
• People Leadership: Minimum of 5 years managing manager-level and architect-level direct reports, with a track record of hiring, mentoring, and retaining top-tier engineering talent
• Change Management Mastery: Documented success in leading complex corporate data migrations or massive MDM implementations across multi-business-unit enterprises
• Experience navigating fast-paced, high-growth environments characterized by rapid organizational restructuring or frequent Mergers & Acquisitions (M&A)
• Expertise in setting up a Data Mesh or federated data architecture in a hybrid or multi-cloud environment
• Active engagement or understanding of integrating AI/ML infrastructure readiness into core enterprise data platforms