Director Enterprise Data Governance

Target•Brooklyn Park, MN

3d•$135,000 - $243,000•Hybrid

About The Position

As the Director of Enterprise Data Governance, you will lead Target’s efforts to ensure data is trusted, accessible, and AI‑ready. You will define the strategy, operating model, and standards that enable accountable, high-quality data at scale—driving faster, higher-confidence decisions and scalable AI through trusted, governed data. Target Tech creates and operates the tools, technology, science, and systems that enable every part of Target’s business and creates compelling and joyful experiences for our team members and guests. Our success is rooted in our diverse and talented team employing architectural discipline, agile execution, innovation, and operational excellence. While we create new capabilities to drive engagement, efficiency, and growth, we also prioritize investing in our technology ecosystem to keep it reliable, performant, and secure. We believe empowering our team to solve problems, fostering continuous learning and innovation, and building strong team culture.

Requirements

10+ years in data management/governance; 5+ in leadership
Four year degree in Business, Tech, Analytics or related field, or equivalent experience
Expertise in data governance, metadata, and lifecycle management
Proficiency with modern cloud data platforms and catalog/quality tools
Knowledge of privacy, risk, and responsible AI
Enterprise leadership and influence across business and technology
Proven change leadership and operating model design
Strong executive communication; outcome‑focused

Responsibilities

Set and execute the enterprise governance vision and roadmap aligned to data strategy and business outcomes
Enable faster, higher-confidence decisions and scalable AI through trusted, governed data
Establish ownership and stewardship across domains with clear accountability
Define and enforce standards for quality, metadata, lineage, access, and lifecycle
Embed governance into platforms, pipelines, and AI/ML workflows
Scale automation (catalog, lineage, data quality, observability)
Provide business direction for governance products and platforms, partnering with product and engineering to drive capability adoption and value
Lead governance forums; align business, product, and technology leaders
Drive enterprise adoption and behavior change toward shared data accountability
Build and lead the governance team and operating model (central + federated)
Define KPIs and maturity model; report outcomes to executives