Senior Enterprise Data Analyst

Overview

This role is part of the Enterprise Data organization and is primarily focused on the overarching governance and architecture of all data across the enterprise.

The Senior Analyst will play a critical leadership role within an Agile data pod supporting the enterprise data environment that underpins Corporate Finance and Regulatory Reporting. This role bridges business, data, and technology to ensure delivery of high-quality, compliant, and scalable data solutions.


Operating at a strategic and execution level, the individual will drive regulatory data remediation, strengthen data governance, and enable Corporate Finance and Regulatory Reporting teams to meet evolving regulatory expectations with confidence and precision.


Responsibilities

Finance andRegulatory Data Strategy & Remediation Leadership

• Lead end-to-end data remediation initiatives focused on accuracy, completeness, and timeliness of regulatory reporting data

• Define and prioritize remediation roadmaps aligned with regulatory commitments (e.g., FR Y-14, Y-9C, Call Reports)

• Provide thought leadership on improving data quality frameworks and control environments

• Partner with senior stakeholders to drive enterprise data maturity

Requirements & Agile Delivery Leadership

• Own requirements lifecycle: intake, decomposition, prioritization, and traceability

• Lead Agile ceremonies and guide backlog prioritization to align with regulatory and business goals

• Translate complex regulatory/data requirements into structured user stories and technical specifications

Data Quality, Governance & Controls

• Design and implement robust data quality rules, controls, and monitoring frameworks

• Strengthen data lineage, reconciliation, and traceability across critical data flows

• Partner with Data Governance teams to enforce standards across metadata, lineage, and critical data elements

• Drive data defects to remediation and closure working with key stakeholders

• Drive adoption of enterprise tools (e.g., Collibra) and governance practices

Stakeholder Engagement & Executive Communication

• Serve as a key interface between Finance, Regulatory Reporting, Technology, and Data

• Influence senior stakeholders and provide clear, actionable insights on data risks and remediation progress

• Lead data and regulatory discussions, including responses to edit checks and supervisory inquiries

• Communicate program status, risks, and dependencies to leadership forums

Root Cause Analysis & Issue Resolution

• Lead deep-dive analyses of data quality issues

• Identify systemic root causes and define sustainable remediation solutions

• Establish issue management frameworks with clear ownership, SLAs, and escalation paths

Data Architecture & Modernization

• Partner with Data and Enterprise Architecture and Engineering teams to drive migration to modern data platforms (e.g., Snowflake, AWS, Azure)

• Ensure modernization initiatives improve data quality, scalability, and regulatory compliance

• Promote adoption of advanced data capabilities including automation and AI/ML where appropriate

Testing, Validation & Documentation

• Define acceptance criteria and oversee validation of data solutions

• Ensure completeness of documentation including:

• Business requirements

• Source-to-target mappings

• Data lineage and metadata

• Support internal audits and regulatory reviews

Qualifications

Bachelor's Degree and 6 years of experience in Data Management, Data Analytics OR High School Diploma or GED and 10 years of experience in Data Management, Data Analytics

Preferred Experience

• 15+ years of experience in data management, data quality, or regulatory data within financial services

• Proven leadership in regulatory reporting data remediation (FR Y-14 strongly preferred)

• Experience working with large, complex banking organizations

Functional Expertise

• Deep knowledge of:

• Finance and Regulatory data in banking industry

• Data quality frameworks and controls

• Data governance and lineage

• Strong understanding of Finance data domains and regulatory expectations

Technical Skills

• Strong SQL and experience with enterprise data platforms:

• Snowflake, Oracle, SQL Server, Netezza

• Familiarity with:

• ETL/data pipelines and data virtualization

• Data governance tools (e.g., Collibra)

• Data visualization (Power BI, Tableau)

• Python / advanced analytics (preferred)

• Experience with cloud platforms (AWS/Azure)

Leadership & Collaboration

• Demonstrated ability to lead cross-functional initiatives across global teams

• Strong executive communication and stakeholder management skills

• Ability to operate in ambiguity and drive outcomes in fast-paced environments

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