Enterprise Data Analyst II

This position leads Bank initiatives that improve enterprise data quality, governance, reporting, and analytics at an advanced level of ability and technical expertise. Drives positive change across the Bank through technical innovation and continuous improvement initiatives, as well as through cross-functional partnership with other business units. Provides expert consultation to team members, the Information Technology department, and other stakeholders on strategies that achieve data management goals. May provide leadership to less experienced consultants in the work group. Responsibilities

Data Enhancement & Analytics

• Leads the implementation of enhancements to enterprise data quality, storage, and management within the Enterprise Data Warehouse.

• Executes initiatives for data profiling, issue resolution, and system fixes.

• Supports and delivers special data-focused initiatives aligned to business needs.

Business Support & Governance

• Enforces enterprise data policies, standards, and governance practices.

• Conducts month-end data validations to ensure accuracy, completeness, and readiness for business use.

• Collaborates with stakeholders to identify gaps and improve data management processes.

• Provides training, guidance, and mentorship to junior team members as needed.

Business Strategy & Stakeholder Collaboration

• Supports the development and execution of enterprise data strategy and roadmap.

• Works cross-functionally to strengthen data management capabilities across business units.

• Maintains current knowledge of emerging technologies, tools, and trends within financial services and data management.

• Serves as a liaison between business, data, and technology teams to ensure alignment and successful delivery.

Documentation & Data Management

• Creates and maintains technical documentation including:

• Source-to-target mappings

• Data dictionaries

• Data lineage and governance artifacts

• Develops and manages centralized, business-critical reporting assets.

Agile Delivery & Execution

• Achieves Agile cadence by actively participating in all ceremonies (sprint planning, daily stand-ups, reviews, and retrospectives).

• Ensures work is managed consistently through Agile frameworks and best practices.

• Performs accurate estimation, backlog refinement, and capacity planning to support reliable delivery.

Backlog Quality & Delivery Readiness

• Establishes and enforces a Definition of Ready (DoR) for all backlog items.

• Ensures at least 90% of user stories meet DoR standards prior to sprint intake, including:

• Clear linkage to parent Jira issue types

• Well-defined acceptance criteria

• User test cases

• Data mapping requirements

• Improves delivery efficiency and reduces rework through consistent backlog quality standards.

Outcome Focus

• Delivers high-quality, reliable enterprise data solutions.

• Improves data integrity, governance, and reporting accuracy.

• Strengthens Agile delivery discipline and predictability.

Bachelor's Degree and 4 years of experience in Data Management, Financial Analysis, or similar OR High School Diploma or GED and 8 years of experience in Data Management, Financial Analysis, or similar

Preferred:

• Experience as Strong Data analyst in Agile environment
• Deep expertise and 15+ years of experience in Data Analysis, Data warehouse and Analytics
• Hardcore data analyst with broad experience desired in data warehousing, documenting business processes, data governance & data integration
• Data wizard with hands on data analysis, profiling, and advanced PL/SQL skills
• Excellent presentation, listening, and writing skills with ability to lead workstreams independently
• Experience with data modelling, data analysis, data visualization, API's and real time services preferred
• Full understanding and hands on experience of waterfall and agile development practices
• Excellent written and verbal communication skills with both internal and external stakeholders
• Domain experience in Customer Data, Marketing Data and systems is highly preferred