Data Governance Manager

Crescent is a differentiated U.S. energy company committed to delivering value through a disciplined, returns-driven growth through acquisition strategy and consistent return of capital. Our long-life, balanced portfolio combines stable cash flows from low-decline production with a deep, high-quality development inventory. Crescent is a top three producer (by gross operated production) in the Eagle Ford basin. Crescent’s leadership is an experienced team of investment, financial and industry professionals that combines proven investment and operating expertise . For more than a decade, Crescent and our predecessors have executed on a consistent strategy focused on cash flow, risk management and returns.    Through disciplined and accretive investments, we have successfully tripled the size of our company since going public in December 2021 while maintaining a strong balance sheet.  The   Data Governance   Manager   is responsible for   establishing , operationalizing, and continuously improving the organization's enterprise data governance and   application   data management capabilities. This role will   lead   the development of governance processes, data stewardship practices, data quality initiatives, and master data programs that ensure trusted, consistent, and business-aligned data across the enterprise.   This position serves as the bridge between business and technology teams, partnering closely with Operations, Engineering, Land, Finance, Regulatory, HSE, and IT to define and govern critical data assets. The Manager will   be responsible for   implementing governance frameworks,   maintaining   enterprise data standards, overseeing data quality management, and ensuring the integrity of master and reference data domains including wells, facilities, assets, vendors, customers, employees, and financial hierarchies.   With   deep   understanding of upstream oil and gas data domains and enterprise data management practices, this role will play a critical part in accelerating the company's journey toward becoming a data-driven, technology-enabled enterprise. This position aligns closely with the enterprise data strategy   and   governance   objectives   established   by the Director of Data & Analytics.   Key Responsibilities:   Enterprise   Data Management   Lead the enterprise Master Data Management strategy and execution across key business domains including wells, assets, facilities, production, land, finance, vendors, and employees.   Establish and   maintain   master data models, hierarchies, business definitions, ownership structures, and governance processes.   Partner with business stakeholders to define and   maintain   authoritative systems of record and systems of reference.   Develop and manage data matching, survivorship, deduplication, and record stewardship processes.   Define and enforce standards for master and reference data creation, maintenance, and retirement.   Support enterprise initiatives involving acquisitions, divestitures, and system integrations by ensuring consistent master data management practices.   Drive the creation of a trusted "single source of truth" for critical enterprise data domains.   Data Governance Program Leadership   Develop and operationalize an enterprise data governance framework including policies, standards, controls, stewardship models, and governance councils.   Facilitate governance committees and working groups to drive alignment across business units.   Define roles and responsibilities for data owners, stewards, custodians, and consumers.   Establish governance workflows for data issue resolution, policy enforcement, and exception management.   Create and   maintain   enterprise data standards, business glossaries, and metadata management processes.   Drive adoption of governance practices across both business and technology teams.   Promote data accountability and stewardship as core organizational capabilities.   Data Quality & Data Trust   Define and manage enterprise data quality strategies, metrics, scorecards, and continuous improvement initiatives.   Establish data quality monitoring processes for completeness, accuracy, consistency, validity, timeliness, and uniqueness.   Partner with Data Engineering,   Analytics and Digital Enablement , and business teams to   identify   and remediate data quality issues.   Implement root-cause analysis processes to reduce recurring data issues.   Develop reporting and dashboards that provide visibility into data quality trends and governance effectiveness.   Establish data quality KPIs and governance performance measures.   Metadata, Catalog & Data Lifecycle Management   Lead the implementation and ongoing management of enterprise metadata, business glossary, and data catalog capabilities.   Maintain data lineage documentation across critical business processes and systems.   Partner with architecture and engineering teams to ensure metadata standards are embedded into the data platform.   Support   information   lifecycle management activities including classification, retention, archival, and disposition processes.   Business Partnership & Data Stewardship   Partner directly with business leaders and subject matter experts to define critical data elements, business rules, and governance priorities.   Build and lead a network of business data stewards across the organization.   Facilitate data governance training and awareness programs.   Support enterprise reporting, analytics, regulatory reporting, and operational decision-making through improved data quality and governance.   Compliance, Risk & Data Controls   Ensure governance processes   support   regulatory, financial, operational, and audit requirements.   Partner with Cybersecurity, Compliance, and Internal Audit teams to support data-related controls and risk management activities.   Assist   in   establi