Location: Hybrid within the M&T/Wilmington Trust footprint, open to remote if based out of footprint

OVERVIEW:

The Wilmington Trust Institutional Services (IS) division is experiencing rapid business growth and has initiated a strategic program of continuous improvement to support the growth objectives. The goals of the program are to reduce operational issues and risks by standardizing processes, implementing best practices in key areas, and adding new governance and control functions. In addition, long term digital transformation is required to grow revenue through new and transformed digital-first trust and agency service products, to move from a product-centric to client-centric operating model, to move from market-specific to global solutions, and to dramatically lower the cost to serve. These two strategic focus areas are driving growth in overall business investment. 

JOB SUMMARY:

In alignment with IS’s growing investment, we are seeking an IS Data Analyst Senior to help the organization understand, govern, and effectively use its data assets. The role identifies where data is stored across the enterprise, organizes and documents the information, analyzes how data moves between applications, and provides practical guidance on data usage, quality, and management practices.  

The successful candidate understands how information is created, transformed, stored, and consumed across business processes and technology platforms. They translate business needs into clear data and functional requirements and support data architecture, governance, reporting, integration, and modernization initiatives.

POSITION RESPONSIBILITIES:

• Identify, inventory, and document where enterprise data is stored across applications, databases, files, reporting platforms, and third-party systems.  

• Analyze data sources and help determine the authoritative source or system of record for critical business information.  

• Develop and maintain data inventories, data catalogs, business glossaries, metadata repositories, and data dictionaries.  

• Assess data quality, completeness, consistency, availability, and usage across business functions.  

• Identify opportunities to improve data accessibility, usability, control, and governance.  

• Analyze how data moves among applications, interfaces, APIs, databases, files, and reporting environments.  

• Document end-to-end data flows, transformations, handoffs, dependencies, and consumption points.  

• Identify gaps, redundancies, control weaknesses, and risks in existing data processes.  

• Collaborate with architects and technology teams to improve data movement and integration approaches.  

• Support impact analysis for system enhancements, migrations, integrations, and new business initiatives.  

• Elicit and analyze business requirements related to data, reporting, analytics, integration, and operational processes.  

• Translate business needs into clear, testable functional and data requirements.  

• Create requirement specifications, use cases, business rules, process flows, data mappings, and acceptance criteria.  

• Act as a liaison between business stakeholders and technology delivery teams.  

• Ensure requirements align with enterprise data standards, approved terminology, and architecture principles.  

• Support data governance initiatives and promote consistent data management practices.  

• Assist in defining and documenting data ownership, stewardship, classification, retention, and accountability.  

• Recommend standards for data quality, metadata management, reference data, and master data.  

• Advise management and technology teams on the appropriate interpretation and use of data.  

• Support audit, regulatory, privacy, risk, and compliance-related data initiatives.  

• Interpret and review conceptual, logical, and physical data models.  

• Partners with data architects, solution architects, and technology teams to ensure business requirements are reflected in data designs.  

• Evaluate the impact of proposed changes to data structures, interfaces, reports, and business processes.  

• Assist in maintaining enterprise data architecture documentation, standards, and reusable artifacts.  

• Serve as a trusted advisor to business and technology teams on data-related questions and decisions.  

• Present findings, recommendations, risks, and options to management and project stakeholders.  

• Facilitate workshops to define data requirements, ownership, data meaning, and business terminology.  

• Promote data literacy and shared understanding across the organization.  

• Understand and adhere to the Company’s risk and regulatory standards, policies and controls in accordance with the Company’s Risk Appetite.  Identify risk-related issues needing escalation to management. 

• Promote an environment that supports belonging and reflects the M&T Bank brand 

• Maintain M&T internal control standards, including timely implementation of internal and external audit points together with any issues raised by external regulators as applicable. 
  Complete other related duties as assigned. 
  

MINIMUM QUALIFICATIONS REQUIRED:

• Bachelor’s degree and a minimum of 5 years related experience, or in lieu of a degree, a combined minimum of 9 years higher education and/ or work experience, including a minimum of 5 years related experience
• Five or more years of experience in data analysis, business analysis, data governance, data management, information management, or a related discipline.  

• Strong understanding of data management principles and the data lifecycle.  

• Experience documenting business, functional, and data requirements.  

• Experience analyzing data flows, system interfaces, and application dependencies.  

• Ability to communicate effectively with both business and technology audiences.  

• Strong analytical, organizational, facilitation, and problem-solving skills 

IDEAL QUALIFICATIONS PREFERRED:

• Intermediate ability to navigate and retrieve data from databases directly and/or through Application Programming Interface (API) 

• Working proficiency with SQL and relational database concepts.  

• Ability to use query languages and data analysis tools to inspect, validate, reconcile, and understand data.  

• Working knowledge of multiple database management systems, such as Microsoft SQL Server, Oracle, PostgreSQL, MySQL, IBM Db2, or cloud data platforms.  

• Ability to read and interpret entity-relationship diagrams, conceptual data models, logical data models, and physical data models.  

• Understanding of data dictionaries, metadata, data lineage, data quality, master data, reference data, and data governance and tools.  

• Understanding of data warehousing, reporting, integration, and data transformation concepts.  

• Understanding of working with data within a workflow solution such as Appian. 

• Experience in financial industry 
  
  

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