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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Regulatory Reporting AVP - Data Governance - **Company:** MUFG Americas - **Location:** Tempe, AZ, United States (Remote available) - **Experience:** Experienced - **Salary:** $87,000.0 - $147,000.0 - **Contract:** Permanent contract - **Skills:** Microsoft Excel, Data Analysis, Data Governance, Decision Support Systems, Metadata, Raw Data, Data Streaming, Enterprise Data Management, Data Lineage, Collibra, Data Management, Tools for Reporting, Data Pipelines - **Published:** May 14, 2026 - **Apply:** https://mufgub.wd3.myworkdayjobs.com/MUFG-Careers/job/Tempe-AZ/Regulatory-Reporting-AVP---Data-Governance_10076482-WD ## About the Role * Approximately 4-6 years of experience in regulatory reporting, capital reporting, finance, or risk functions within a banking or financial services environment. * Working knowledge of data governance concepts, including data quality, lineage, metadata, and controls. * Familiarity with regulatory expectations related to data governance and risk data aggregation (e.g., BCBS 239). * Experience with data governance and reporting tools such as Collibra, Excel, Axiom, or similar platforms. * Strong written and verbal communication skills, with the ability to collaborate effectively across functions and escalate issues appropriately. Education: * Bachelor's degree in Accounting, Finance, Economics, or a related field; advanced degree, CPA, or CFA preferred. The above statements are intended to describe the general nature and level of the work being performed. They are not intended to be construed as an exhaustive list of all responsibilities, duties, and skills required of personnel so classified. ## Description The Regulatory Reporting AVP, Data Governance will work in the Enterprise Reporting Analytics (ERA) team in Chief Data Office (CD) to support the ERA Data Officer in executing the ongoing management of the firm's enterprise data governance framework, with a particular focus on regulatory and risk-critical data. This includes contributing to data quality, lineage, metadata, and control initiatives, supporting regulatory expectations related to data governance, accountability, and risk data aggregation., * Support the implementation and ongoing execution of the enterprise data governance framework, with a focus on regulatory and risk-critical data domains. * Partner with Enterprise Data Owners, Data Officers, and Data Stewards to establish and maintain clear data ownership, stewardship roles, and accountability structures for Critical Data Elements (CDEs). * Contribute to the development, documentation, and maintenance of authoritative data definitions, business glossaries, data standards, and metadata in approved governance tools (e.g., Collibra). * Promote consistent adoption of data governance standards across regulatory reporting, risk, and finance use cases, ensuring alignment with enterprise policy and regulatory expectations. Data Quality & Controls * Support the design, implementation, and monitoring of data quality rules, thresholds, and key performance indicators (e.g., accuracy, completeness, timeliness, consistency) for regulatory and risk-critical data. * Assist in embedding data quality controls within upstream systems, data pipelines, and reporting processes, in coordination with Technology and business stakeholders. * Monitor data quality performance and trends, support root-cause analysis of data quality issues, and assist in defining remediation actions and sustainable control enhancements. * Contribute to data quality reporting and management information provided to senior management, data governance forums, and regulatory stakeholders as needed. Data Lineage & Regulatory Readiness * Support the documentation and maintenance of end-to-end data lineage for regulatory reports, risk calculations, and management reporting, from source systems through transformations to final consumption. * Ensure lineage artifacts clearly demonstrate data flows, controls, and dependencies in a manner that meets internal governance standards and external regulatory expectations (e.g., BCBS 239). * Maintain lineage, metadata, and related governance artifacts within approved enterprise tools, ensuring accuracy, completeness, and ongoing currency. * Prepare and coordinate documentation, evidence, and responses to support internal audits, model validations, data quality reviews, and regulatory examinations. Change & Issue Management * Support data governance impact assessments related to regulatory changes, new reporting requirements, system implementations, platform migrations, and changes to data sourcing or calculation logic. * Assist in identifying, documenting, and escalating data-related risks and issues, including data quality breaks, lineage gaps, control deficiencies, audit findings, and regulatory observations. * Track remediation efforts through established issue management and governance processes, coordinating with business, technology, and risk partners to ensure timely and effective resolution. * Contribute to lessons-learned analysis and continuous improvement initiatives to strengthen data governance, controls, and sustainability outcomes. Cross-Functional Collaboration & Communication * Partner closely with Regulatory Reporting, Capital Management, Risk, Finance, Technology, and other control functions to promote consistent data standards, definitions, and governance practices across the enterprise. * Act as a point of coordination between the ERA Data Officer and key stakeholders to facilitate alignment on data governance priorities, regulatory commitments, and execution timelines. * Support preparation of materials for data governance committees, working groups, and senior management forums, including status updates, risk assessments, and decision support materials. * Contribute to strengthening the firm's data culture by reinforcing accountability, transparency, and proactive risk management in the use of regulatory and risk-critical data. ## Related Videos - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Detecting Money Laundering with AI](https://www.wearedevelopers.com/videos/111-detecting-money-laundering-with-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) - [From Global Capability Centers to AI-Powered Command Centers](https://www.wearedevelopers.com/videos/100096-from-global-capability-centers-to-ai-powered-command-centers) - [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) ## Related Articles - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [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) - [Data Analyst Salary Austria](https://www.wearedevelopers.com/magazine/275-data-analyst-salary-austria) - [Data Analyst Salary in Switzerland](https://www.wearedevelopers.com/magazine/276-data-analyst-salary-in-switzerland) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)