Program Manager, Data Governance and Stewardship, US Based

ReSource Pro•, MO

5d•$11 - $24•Remote

About The Position

ReSource Pro is seeking a Data Governance and Stewardship Lead to establish and maintain the frameworks, standards, and practices that support the integrity, security, compliance, and appropriate use of ReSource Pro’s data. This role translates data governance principles into practical policies, controls, stewardship practices, and data quality standards that can be consistently applied across a complex, data-intensive environment. The role works cross-functionally with Data Strategy, Technology, Security, Legal, Compliance, and business stakeholders to define and maintain governance standards for how data is collected, classified, accessed, used, retained, and retired. The Data Governance and Stewardship Lead also supports data quality, lineage, documentation, and stewardship practices that enable the effective use of data for analytics, reporting, automation, and AI. The role applies strategic and hands-on expertise to establish and maintain data governance practices, translate complex governance requirements into practical policies and guidance, and support consistent adoption and accountability across the organization. All remote positions are based in the United States, and candidates must reside within the U.S. to be considered.

Requirements

Bachelor’s degree in Data Management, Information Systems, Computer Science, Business Administration, or a related field preferred.
5–8 years of experience in data governance, data stewardship, data management, data quality, or a related discipline.
Experience working in the insurance industry preferred.
Experience supporting data governance for analytics, automation, machine learning, or AI use cases.
Familiarity with data governance frameworks, data management best practices, or relevant industry standards.
Experience implementing or improving data governance programs in a growing or changing organization.
Hands-on experience developing, implementing, or maintaining data governance frameworks, policies, standards, and controls.
Experience establishing practices related to data quality, classification, access, retention, privacy, or lifecycle management.
Working knowledge of data privacy, security, regulatory, and compliance requirements in a regulated or data-intensive environment.
Experience with data catalogs, metadata management, data lineage, data quality tools, or related data management technologies.
Strong data fluency, including the ability to understand data structures, relationships, sources, and downstream use; experience with SQL is preferred.
Ability to translate complex governance, privacy, security, and data management requirements into clear policies and practical guidance.
Strong analytical and problem-solving skills, with the ability to identify root causes and drive sustainable remediation.
Excellent written and verbal communication skills, including the ability to work effectively with both technical and non-technical stakeholders.
Strong attention to detail and a disciplined approach to documentation, process, and follow-through.
Ability to work independently, manage multiple priorities, and influence stakeholders across functions without direct authority.
Technological proficiency – able to learn, utilize, and navigate a variety of external and internal systems

Nice To Haves

Experience working in the insurance industry
Experience supporting data governance for analytics, automation, machine learning, or AI use cases.
Experience with SQL

Responsibilities

Build and Maintain the Data Governance and Stewardship Framework: Develop, document, and maintain data governance policies, standards, procedures, and controls that support the appropriate collection, classification, storage, access, use, retention, and retirement of data. Define and maintain data ownership, accountability, stewardship, and quality responsibilities across business and functional areas. Establish practical and scalable governance practices that can be consistently applied across a complex, data-intensive organization. Maintain clear documentation of governance requirements, decision rights, standards, and operating practices. Partner with data owners, stewards, and cross-functional stakeholders to implement governance standards and resolve data-related issues. Develop guidance and education that help stakeholders understand and fulfill their data governance and stewardship responsibilities.
Drive Data Quality, Lineage, and Data Lifecycle Management: Define and maintain data quality standards, rules, and processes for critical data assets. Establish monitoring and control mechanisms to identify data errors, gaps, inconsistencies, and other quality issues. Partner with data owners and stewards to investigate root causes, prioritize remediation, and improve data quality over time. Maintain data lineage and documentation to improve traceability from source systems through downstream use. Support the development and maintenance of data catalogs, business glossaries, metadata, and other documentation that improve understanding and accessibility of governed data. Help ensure data assets can be traced, understood, and appropriately governed throughout their lifecycle. Monitor adherence to established data governance and quality standards and communicate findings, risks, and remediation needs to relevant stakeholders.
Support Data Privacy, Security, Client Commitments, and Responsible Data Use: Partner with Security, Legal, Compliance, and other stakeholders to support data privacy, security, risk management, and regulatory requirements. Translate contractual and client-specific data requirements into clear governance standards, controls, and operating practices. Support governance of how client and company data may be accessed, used, stored, shared, retained, and retired. Maintain appropriate documentation and evidence to demonstrate adherence to applicable data requirements and commitments. Identify and escalate governance risks, gaps, and potential areas of non-compliance. Partner with analytics, technology, and AI teams to ensure data used for automation, analytics, and AI applications meets applicable governance, privacy, security, quality, and documentation requirements. Support governance practices that promote responsible and explainable use of data in AI-enabled solutions.
Monitor Adoption and Continuously Improve Governance Practices: Develop metrics, reporting, and other mechanisms to monitor governance adoption, data quality, and areas of risk or improvement. Track adherence to data governance standards and support remediation where practices fall short. Serve as a trusted advisor and subject matter expert on data governance and stewardship questions. Promote data literacy and effective stewardship practices through clear documentation, training, and engagement. Facilitate collaboration among data owners, stewards, and technical teams to resolve governance and data quality issues. Continuously refine governance practices as regulations, client requirements, business needs, and technology evolve.
Teamwork & Collaboration (Standard): Foster a respectful and collaborative environment by upholding professionalism and engaging in constructive and respectful conversations. Support a positive workplace culture by promoting open, solution-oriented communication, encouraging teamwork, and maintaining a focus on shared goals and productivity.