Enterprise Data Governance Manager Sr

Doosan Corp•Minneapolis, MN

13d

About The Position

At Doosan Bobcat, our success is powered by our people. Through our winning culture and one global team working together, we deliver the best products and service to our customers – and make the world a better place. Join our team today and start building your career with a worldwide leader. Job InformationThe Enterprise Data Governance Manager Sr is expected to establish, operationalize, and lead enterprise data foundations that support both AI capabilities and traditional reporting/analytics. This role is responsible for ensuring data – structured, semi-structured, and unstructured - is trusted, well‑defined, discoverable, secure, and ready for consumption. Success in this role requires building practical frameworks, clear ownership models, and repeatable practices that enable teams to move fast with confidence and effective risk management.Role & Responsibility

Requirements

Bachelor’s degree in Computer Science, Information Technology, or a related field; Master’s degree preferred.
10+ years of experience in data, analytics, AI, or information management roles.
Proven experience establishing data governance policies and designing secure, high-availability data systems.
Demonstrated expertise in establishing and operating enterprise data governance frameworks
Direct experience in identifying, storing and managing metadata and data lineage.
Strong understanding of analytics platforms, semantic layers, and ecosystems supporting both AI and traditional analytics.
Experience supporting both structured and unstructured data usage in AI and knowledge systems.
Strong leadership, change management, mentoring, and communication skills with a demonstrated ability to influence cross‑functional teams.
Comfortable working in an ambiguous, fast-paced, and changing environment
Ability to balance immediate business needs with long‑term enterprise data governance strategy.
Experience working in Agile delivery environments.
Familiarity with modern data platforms and tooling such as Snowflake and dbt.
Willingness to travel up to 25%.

Nice To Haves

Prosci or equivalent change management certification preferred.

Responsibilities

Define and own the enterprise data governance strategy spanning structured, semi‑structured, and unstructured data. Includes the establishment of Bobcat’s ontology.
Design, document, and reinforce enterprise data usage practices including data definitions, quality expectations, lineage transparency, and access controls so Bobcat teams can effectively consume data for AI, analytics, dashboards, and operational reporting.
Work closely with Legal and risk management teams to support data privacy and compliance requirements while reinforcing innovation, speed, and usability
Ensure strategic alignment with Bobcat’s Enterprise Master Data Management team initiatives
Partner with AI Center of Excellence and Digital teams to ensure data inputs and outputs are traceable, explainable, and trusted
Work directly with AI and analytics builders to ensure data is used responsibly, efficiently, and at enterprise scale by:
Applying data classification standards to AI use cases so teams understand what data can be used, how, and under what conditions
Identifying data‑related risks early (e.g., privacy, sensitivity, misuse, localization) and guiding teams toward compliant design choices
Surfacing opportunities to streamline data usage, reducing redundant data pipelines, duplicate feature engineering, and inconsistent approaches
Shaping globally scalable data designs, ensuring AI solutions account for regional data requirements, reuse patterns, and future expansion
Design and maintain enterprise approaches for identifying and capturing business definitions, metrics logic and semantic consistency
Define how different data types are classified, owned, accessed, and refreshed
Work with Bobcat teams to successfully implement defined data practices
Establish clear accountability and operating model across data domains aligning business, AI and Digital stakeholders to maximize the value of Bobcat’s data
Embed data accountability into delivery teams and workflows
Connect and build trusted relationships with key stakeholders from various Bobcat Lines of Business
Lead awareness and enablement sessions so Bobcat teams understand how to classify and use data responsibly and effectively
Replace policy‑heavy approaches with clear guidance, examples, and tooling alignment
Put mechanisms in place to identify, surface, and address data quality issues
Track and demonstrate impact through improved trust, reuse, and decision quality