Director of Data Platform & Governance

Director of Data Platform & Governance

Job Overview: The Director of Data Platform & Governance is responsible for the strategic leadership, design, and operational maturity of the organization’s enterprise data capabilities. This role owns the data platform (data lake, warehouse, integration pipelines), enterprise data governance, and is responsible for enabling AI‑powered analytics across the organization.

Reporting into IT leadership, this role partners closely with IT Operations, Security, Cloud Governance, and Business Leaders to ensure data is treated as trusted enterprise infrastructure‑secure, governed, scalable, and cost‑effective.

AI is not treated as a standalone function; instead, this role ensures AI‑enabled capabilities are safely integrated into the data platform with appropriate governance, controls, and architectural standards.

Job Details

• Define and own the enterprise data strategy and roadmap
  , aligned to business outcomes and technology standards
• Establish data as a shared enterprise capability
  , balancing central control with federated business consumption
• Serve as the executive‑facing leader for data, analytics, and AI enablement initiatives

• Own the architecture and evolution of:
  • Enterprise data warehouse and data lake
  • Data integration and ingestion pipelines
  • Metadata, lineage, and data quality frameworks
• Ensure platform designs align with:
  • Cloud governance guardrails
  • Infrastructure standards
  • Security and compliance requirements
• Guide architectural decisions related to AI‑enabled analytics
  , including:
  • AI‑ready data design
  • Approved AI integration patterns
  • Vendor vs in‑house capability decisions

• Establish and enforce enterprise data governance
  , including:
  • Data ownership and stewardship models
  • Classification, access controls, and lifecycle management
  • Data quality standards and SLAs
• Extend governance practices to AI‑enabled data usage
  , including:
  • Acceptable use policies
  • Data usage constraints for AI systems
  • Documentation and audit readiness
• Partner with Security, Legal, and Compliance on regulatory and risk considerations

• Enable AI‑powered analytics by ensuring:
  • Trusted, governed data inputs
  • Secure access patterns
  • Operational readiness and cost controls
• Ensure AI workloads integrate into:
  • Existing data platforms
  • Monitoring and logging frameworks
  • Change and incident management processes
• Act as a control point to prevent AI sprawl, shadow systems, and unmanaged risk

• Lead and develop a team of data engineers, platform engineers, and governance resources
• Establish Data Ops practices for:
  • Reliability
  • Observability
  • Cost transparency
  • Incident and problem management
• Partner with IT Operations to treat the data platform as a Tier‑1 enterprise service

• Serve as the primary interface between:
  • IT Operations
  • Security
  • Cloud Governance
  • Business and analytics stakeholders
• Communicate clearly with executives on:
  • Risk
  • Investment trade‑offs
  • Platform maturity
  • Value delivery

Required

• 10+ years of experience in data engineering, analytics platforms, or data architecture
• 5+ years in a leadership role managing data teams and enterprise platforms
• Proven experience with:
  • Enterprise data warehousing and/or lakehouse architectures
  • Large‑scale data integration and pipeline orchestration
  • Data governance frameworks and operating models
  • Hands‑on experience enabling AI or advanced analytics using governed enterprise data

• Strong understanding of:
  • Cloud‑based data platforms (Azure or AWS)
  • Data modeling, ingestion, and transformation patterns
  • Metadata management, lineage, and data quality tooling
• Working knowledge of:
  • AI‑enabled analytics concepts (e.g., feature data, embeddings, inference inputs/outputs)
  • Security controls related to data access, encryption, and logging
• Ability to translate complex technical concepts into executive‑level decisions

• Demonstrated ability to:
  • Build and scale high‑performing technical teams
  • Balance innovation with governance and risk management
  • Influence without direct authority
  • Strong communication skills across:
    • Technical teams
    • Executives
    • Non‑technical stakeholders
  • Comfortable operating in environments with evolving requirements and priorities

• Experience implementing formal data governance programs
• Familiarity with ITIL, service management, or regulated environments
• Experience aligning data platforms with cloud financial management (Fin Ops)
• Exposure to AI governance, responsible AI, or audit readiness frameworks
• Prior experience partnering closely with Security and Infrastructure teams