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
Strategic Leadership & Vision
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
Data Platform & Architecture
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
Data Governance & Risk Management
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
AI Enablement (Embedded, Not Standalone)
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
Operational Excellence & Delivery
Lead and develop a team of data engineers, platform engineers, and governance resources
Establish DataOps 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
Stakeholder & Executive Partnership
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
Job Requirements Required
Experience
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
Technical & Domain Expertise
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
Leadership & Business Skills
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
Desired
Experience implementing formal
data governance programs
Familiarity with ITIL, service management, or regulated environments
Experience aligning data platforms with
cloud financial management (FinOps)
Exposure to AI governance, responsible AI, or audit readiness frameworks
Prior experience partnering closely with Security and Infrastructure teams
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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
Strategic Leadership & Vision
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
Data Platform & Architecture
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
Data Governance & Risk Management
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
AI Enablement (Embedded, Not Standalone)
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
Operational Excellence & Delivery
Lead and develop a team of data engineers, platform engineers, and governance resources
Establish DataOps 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
Stakeholder & Executive Partnership
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
Job Requirements Required
Experience
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
Technical & Domain Expertise
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
Leadership & Business Skills
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
Desired
Experience implementing formal
data governance programs
Familiarity with ITIL, service management, or regulated environments
Experience aligning data platforms with
cloud financial management (FinOps)
Exposure to AI governance, responsible AI, or audit readiness frameworks
Prior experience partnering closely with Security and Infrastructure teams
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