Technical Data Strategy & Governance Program Manager

Minneapolis, MN (Hybrid). Local candidates are highly preferred due to onsite expectations.

This is a hands-on role requiring strong experience in data strategy, governance, and enterprise data architecture, along with active involvement in program execution and stakeholder engagement.

Candidates should have proven experience in driving data initiatives, working closely with cross-functional teams, and delivering high-quality outcomes aligned with business goals.

Role Summary

The Data Strategy Program Leader is a senior leadership role responsible for developing, driving, and governing the organization''s overarching data strategy and architecture. This role ensures that data is managed as a strategic asset, enabling data-driven decision-making, competitive advantage, and alignment with overall business objectives. This leader manages a program of data-related initiatives, oversees cross-functional collaboration, and champions data governance, quality, and literacy across the enterprise.

An experienced leader who has hands-on experience developing and delivering data strategies. This person will guide the team on the work, organize and manage the overall program, and ensure deliverables are completed on time and with a high level of quality.

Key Responsibilities

1. Strategy & Planning

· Develop Data Strategy: Define and lead the implementation of a comprehensive data strategy, architecture, and roadmap that supports business goals, focusing on improving the management, governance, and security of information.

· Strategic Alignment: Work closely with the leadership team (e.g., Chief Data Officer, Business Partners) to understand business needs, use cases, and data flows, ensuring all data initiatives directly drive strategic priorities.

· Program Management: Plan, coordinate, and manage all activities related to the strategic integration of data across various sources, including new data stores and cloud services, to form a unified, single source of truth.

2. Governance & Compliance

· Establish Governance: Develop, define, and implement data governance policies, standards, and best practices across the organization.

· Data Quality & Security: Drive standards for data quality, integrity, and security, and ensure compliance with regulatory standards (e.g., GDPR, CCPA).

· Architecture Oversight: Design and oversee the data architecture frameworks, ensuring that data models (Conceptual, Logical, Physical) and systems are scalable, secure, and performant.

3. Stakeholder Management & Leadership

· Relationship Management: Establish trusted partnerships with key stakeholders across the business and IT to understand their data needs and advocate for their priorities.

· Advocacy & Communication: Effectively communicate the status, value, and importance of the data strategy and its programs to the leadership team, senior managers, and staff.

· Team Guidance: Lead, manage, and mentor cross-functional teams, including Data Analysts, Data Engineers, and Information Governance Analysts, to ensure adherence to data standards and successful project delivery.

· Data Literacy: Manage a program to train and upskill staff on data-related competencies, policies, standards, and the use of business intelligence (BI) tools.

4. Analytics & Innovation

· Insight Generation: Lead the continuous evolution of the analytics framework to allow stakeholders to leverage data for improved decision-making, operational efficiency, and results monitoring.

· Innovation: Identify opportunities for the organization to leverage its data assets, including exploring and implementing pilots in the data analytics and Artificial Intelligence (AI) innovation space.

Required Skills and Experience

· Education: Bachelor''s degree in Data Science, Computer Science, Statistics, Business, or a related field. An advanced degree (MBA, Master''s, or PhD) is often preferred.

· Data Management Expertise: Strong, proven experience in developing and implementing enterprise-level data strategies and architectures, including a deep understanding of data warehousing, data lakes, and both relational and NoSQL databases.

· Governance & Compliance: Solid knowledge of data governance principles, metadata management, and data privacy regulations.

· Technical Proficiency: Familiarity with data analysis tools (e.g., Python, R, SQL), data visualization platforms (e.g., Tableau, Power BI), and cloud-based data solutions (e.g., AWS, Azure, Google Cloud Platform).

· Leadership & Communication: Exceptional presentation, written, and verbal communication skills with a proven ability to translate complex data issues into business value for non-technical audiences.

· Program/Project Management: Strong project and program management skills with the ability to oversee multiple complex initiatives simultaneously.

Skill Matrix to be filled by Candidates: