Data Governance Analyst

** Essential Duties and Responsibilities*
* + Fully understand various data and reporting flows across the Regulatory Reporting areas to identify data sourcing and full lineage to consumption.

+ Support the identification and documentation efforts for all Enterprise data sets and use cases

+ Analyze and document end-to-end use case data flows from target to source into a Business Glossary document, identifying and documenting the data lineage and transformations, and data quality rules that are required, as well as improvement opportunities throughout the data flow.

+ Use Ab Initio tool to load data catalogs, required business terms / definitions, link business to technical data elements, categorizing criticality of each data element, and working with IT to complete the data lineage from data sources to reports

+ Correspond and execute deliverables aligned with principles, policies, frameworks and procedures laid at the firm or business unit or function levels as per the guidance from the Chief Administrative Officer heading up the Business Controls & Risk function.

+ Collaborate with appropriate business stakeholders/remediation owners to implement data quality controls, help remediate data gap issues and improve processes to prevent future data concerns.

+ Track, resolve and escalate issues for own projects while keeping relevant stakeholders informed.

+ Maintain project deliverables including reporting and tracking status using PowerPoint, Excel, SharePoint, and Teams Planner

+ Create effective presentations to be used with business audiences of various levels.

+ Support day-to-day activities that align to data governance and management activities, various end-to-end data efforts, and optimize metrics and progress reporting processes.

+ Monitor and support governance of data management processes

+ Identify opportunities to improve governance processes, efficiency, and execution rigor

+ Facilitate discussions with cross-functional stakeholders to evaluate data use cases, risks, and compliance requirements.

** Knowledge of*
* + Foundational data quality principles and how they contribute to 'fit for purpose' data.

+ Data development lifecycle - requirements, source analysis, data design, ETL development, test & validation, deployment, monitoring & operations, governance & stewardship

+ Concepts, principles and practices of internal controls and data management and governance.

+ Principles of banking, finance and securities industry operations, and familiarity with accounting and finance related topics.

+ General familiarity with risk and control framework of Category IV financial institution.

+ Concepts of business analytics and familiarity with business intelligence tools such as Python, Tableau, Qlik, MS Power BI, MS Teams, SharePoint, etc.

+ Experience in using data gap remediation and data quality monitoring tools (particularly Microsoft Dev Ops (TFS), Ab Initio, Collibra, IBM Info Sphere or Informatica Data Quality) is a plus.

+ Familiarity with Federal Reserve Bank (FRB) and/or Office of the Comptroller of the Currency (OCC) regulatory requirements or other regulatory bodies is a plus.

** Skill in*
* + Hands-on expertise in leveraging Domain Specific Languages such as SQL to retrieve, combine and manipulate large data sets.

+ Deep understanding of enterprise data management concepts, principles and current industry practices.

+ Strong "soft" skills in collaboration, facilitation, coordination, logistics, presentation, marketing, and excellent communication skills (both written and verbal).

+ Experience delivering data quality improvements in a complex, transforming, multi-national banking environment.

+ Organizational and planning skills, showing an ability to operate in a multi-geography, matrix organization; managing and where necessary leading activities through cross-functional teams, with the discipline to track delivery of complex deliverables over multiple months.

+ Excellent communication skills (both written and verbal), including the ability to present complex concepts and strategies successfully.

+ Demonstrated strong execution capabilities and entrepreneurial mindset to go above and beyond delivering core responsibilities.

** Ability to*
* + Analyze, problem-solve and prioritize

+ Demonstrate strong analytical thinking and autonomy in translating problems into efficient, executable solution

+ Understand data models and taxonomies, with deep skills in data quality, controls and remediation

+ Produce and articulate meaningful data quality metrics and KPIs

+ Help drive data quality strategy and foster data culture across the organization