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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Governance Specialist/Lead - **Company:** RR Donnelley - **Location:** Warrenville, IL, United States (Remote available) - **Experience:** Expert - **Salary:** $85,000.0 - $136,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Cloud Database, Data Dictionary, Data Governance, Data Security, Metadata, Meta-Data Management, DataOps, Data Lineage, Collibra, SAP MDG, Data Management - **Published:** July 29, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=728819c84c86ae1b ## About the Role * Education: BA/BS degree required. * General Experience: 5+ years of experience in consulting or with large enterprise data governance programs preferred. * Data Governance Tool Experience: Experience with Collibra, Informatica's Cloud Data Governance and Catalog (CDGC) or similar tools. Experience with MDM tools is a plus. * Proven Standardizer: Battle-tested in leading large scale, successful data standardization projects across messy, disparate systems. * Technical Authority: Deep, practical knowledge of metadata management, data observability, and enterprise taxonomy design. * Mindset & Leadership: A "Pragmatic Builder" focused on incremental, sustainable value delivery rather than highly disruptive transformations. * Exceptional Soft Skills: Must be a "Cross-Functional Unifier" and a "Business Translator" capable of clearly articulating how standardized data directly enables high-value AI and reporting outcomes. * Insatiably Curious: Enjoys learning and diving into the unknown. Has a strong desire to deeply understand complex ideas and processes. ## Description As a Data Governance Specialist/Lead you will help to build the foundation for the future of data and AI. RRD is experiencing a paradigm shift from traditional reporting and dash-boarding to dynamic, autonomous AI applications. To fuel this transformation, we need a Data Governance Lead to ensure our data can "stand on its own" for unknown and unimaginable future AI purposes. To do this, the data must be well documented, its metadata well maintained, and its taxonomies and ontologies clearly defined., * Establish Strong Foundations: Lead the early formalization of enterprise data governance, active metadata management, data quality documentation and management and the definition of data access rights to ensure trusted, understood and usable data. * Standardize and Formalize: Socialize data related standards by defining foundational taxonomies, data dictionaries, data lineage documentation and ontologies. * Continuously Assess Readiness: Design and manage a continuous Data Governance Lifecycle (Establish, Operate, Iterate) to certify data readiness for AI during the operationalization of production use cases. * Evolve Incrementally: Continuously refining existing standards, gathering lessons learned, and seamlessly adding new domains as data requests are prioritized. * Build Multidisciplinary Teams: Empower and unite cross-functional teams, including data stewards, engineers, AI specialists, and business domain experts, to build truly AI-ready data products. Lead metadata harmonization workshops with data stewards, senior leaders, and SMEs to resolve definition conflicts and align standards. * Change Agent: Be the change agent to enable user adoption of data governance processes, procedures, controls such as those related to metadata, data quality, and data ownership. * Compliance: Work to ensure that data is compliant with all applicable requirements including CCPA, SOX, GDPR, HIPAA. ## Related Videos - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Crafting Custom Frameworks with Rust: A Deep Dive into Procedural Macros](https://www.wearedevelopers.com/videos/849-crafting-custom-frameworks-with-rust-a-deep-dive-into-procedural-macros) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Bringing Clarity to Event Streams: Enabling Analytics and AI Through Rich Metadata](https://www.wearedevelopers.com/videos/1616-bringing-clarity-to-event-streams-enabling-analytics-and-ai-through-rich-metadata) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)