> Markdown version of [/jobs/ext/4545444-avp-data-governance-change-management-nj](https://www.wearedevelopers.com/jobs/ext/4545444-avp-data-governance-change-management-nj). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AVP Data Governance Change Management - NJ - **Company:** MUFG Americas - **Location:** Jersey City, NJ, United States (Remote available) - **Experience:** Expert - **Salary:** $110,000.0 - $142,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Microsoft Azure, Databases, Data Architecture, Data Governance, Data Integration, Extract Transform Load (ETL), Data Structures, Data Warehousing, Relational Databases, Data Flow Control, Information Lifecycle Management, Systems Analysis, Logical Data Models, Metadata, Systems Development Life Cycle, Cloud Services, SQL Databases, Data Streaming, Systems Integration, Unstructured Data, Enterprise Data Management, Enterprise Software Applications, Informatica Powercenter, Snowflake, Data Lakes, Information Technology, Data Lineage, Collibra, Apache Kafka, Operational Systems, Data Management, Data Pipelines, Databricks - **Published:** November 3, 2026 - **Apply:** https://mufgub.wd3.myworkdayjobs.com/MUFG-Careers/job/Jersey-City-NJ/AVP-Data-Governance-Change-Management---NJ_10080369-WD ## About the Role * 5-7+ years of relevant experience in data management, systems analysis, data governance, data architecture, technology delivery, business analysis, or related disciplines. * Strong understanding of enterprise application architectures and system-to-system data movement, including upstream and downstream dependencies. * Working knowledge of common data integration concepts, including APIs, batch interfaces, ETL/ELT, data pipelines, file-based exchanges, databases, data warehouses, and cloud data platforms. * Ability to interpret logical architecture diagrams, data-flow diagrams, system context diagrams, conceptual/logical data models, and interface documentation. * Working knowledge of relational data concepts and SQL. Ability to understand queries, tables, joins, schemas, and data relationships is strongly preferred; advanced development skills are not required. * Understanding of structured and unstructured data, metadata, data lineage, data quality, reference/master data, and data lifecycle concepts. * Experience working with SDLC, technology change, architecture review, or enterprise project governance processes. * Experience reviewing technical and project artifacts and translating technical changes into business, data, governance, and downstream impact assessments. * Strong ability to communicate with engineers, architects, project managers, product owners, and business stakeholders and translate across technical and non-technical audiences. * Demonstrated ability to investigate an unfamiliar system or process and quickly develop an understanding of its purpose, data inputs, outputs, dependencies, and consumers. Preferred Technical Experience * Experience with enterprise data governance/catalog platforms such as Collibra or comparable metadata-management platforms. * Familiarity with data lineage and technical metadata tooling. * Experience with enterprise data warehouses, data lakes/lakehouses, cloud data platforms, or shared analytical environments. * Familiarity with platforms and technologies such as Snowflake, Databricks, Azure, AWS, Informatica, Kafka, or comparable enterprise data technologies. * Familiarity with architecture repositories, CMDBs, project portfolio management systems, or enterprise technology inventories. * Experience working in a complex financial-services or other highly regulated technology environment. Education: * Bachelor's degree in Computer Science or a closely-related discipline, or an equivalent combination of formal education and experience "Visa sponsorship/support is based on business needs. We do not anticipate providing visa sponsorship/support for this position." ## Description The AVP, Data Governance Change Management will serve as a key point of engagement between the Data Office and enterprise change initiatives, assessing changes to business processes, applications, technology, and data for potential impacts to the organization's data governance capabilities and enterprise data platforms. The role requires a strong combination of data management, systems analysis, technical acumen, and project delivery experience. The individual should be comfortable reviewing application architectures, system interfaces, data flows, integration patterns, and project solution designs to identify potential impacts to enterprise data capabilities. Where impacts are isolated to a single data domain, the AVP will facilitate a warm transition to the appropriate domain team. Where changes affect enterprise data platforms, shared capabilities, integrations, or multiple domains, the AVP will remain engaged to ensure impacts and dependencies are appropriately addressed throughout the project lifecycle. Strengthened Technical Responsibilities * Review solution designs, architecture diagrams, data-flow diagrams, interface specifications, system inventories, and project requirements to identify potential data impacts. * Understand how data moves between source applications, integration layers, enterprise data platforms, analytical environments, and downstream consumers. * Evaluate changes to data sources, interfaces, APIs, ETL/ELT processes, data models, feeds, pipelines, and system integrations for potential governance and platform impacts. * Identify potential changes to data lineage, metadata, data quality, authoritative sources, data ownership, critical data, and downstream consumption. * Partner with enterprise architecture, solution architecture, engineering, and application teams to understand proposed technology changes and their data implications. * Assess whether projects introduce new data sources, modify existing data structures or flows, decommission systems, or create new dependencies on enterprise data platforms. * Apply sufficient technical knowledge to challenge project assumptions, identify gaps, and determine when deeper engagement from a data architect, engineer, platform owner, or domain specialist is required. * Maintain a broad working understanding of the enterprise application landscape and relationships between key operational systems and enterprise data platforms. * Use enterprise metadata, lineage, catalog, and architecture information to support project impact assessments.