Senior Data Management Business Analyst (Onsite Local)

Position Summary
The Enterprise Data & Analytics Services (EDAS) organization is seeking an experienced Senior Data Management Business Analyst to support strategic data initiatives, enterprise modernization efforts, data governance programs, and Data Supply Chain delivery activities. This role serves as a critical liaison between Business Stakeholders, Data Engineers, Data Modelers, Data Architects, Product Owners, Governance teams, and delivery partners. The successful candidate will transform business needs into actionable data requirements, perform analysis across complex enterprise data environments, document current and future-state data flows, and support the successful delivery of enterprise data initiatives. The ideal candidate possesses deep experience in data analysis, data management, and business analysis, with the ability to understand how data moves throughout the enterprise. This individual should be comfortable reviewing existing integrations, analyzing Ab Initio data flows, developing source-to-target mappings, supporting Critical Data Element (CDE) governance activities, utilizing enterprise data catalog capabilities, and partnering with technical teams to design scalable and maintainable data solutions. Experience with Google Cloud Platform (Google Cloud Platform) and BigQuery is beneficial.

Key Responsibilities
Business Analysis & Stakeholder Engagement
Partner with business stakeholders to understand strategic objectives, business challenges, regulatory requirements, information needs, and desired business outcomes.
Facilitate discovery sessions, stakeholder workshops, interviews, and data requirements discussions.
Elicit, analyze, document, and validate enterprise data requirements, including data sourcing needs, business rules, Critical Data Elements (CDEs), data quality expectations, metadata requirements, and lineage considerations.
Translate business needs into actionable data specifications, source-to-target mappings, transformation logic, data quality controls, and consumption requirements supporting analytics, reporting, governance, and operational use cases.
Develop data flow diagrams, business process flows, business rules, and operational procedures.
Facilitate alignment among stakeholders regarding data definitions, sourcing strategies, governance requirements, and downstream data usage.
Communicate findings, recommendations, risks, dependencies, and impacts to both technical and non-technical audiences.
Create executive-ready presentations, impact assessments, status reporting, and decision-support materials.

Data Analysis & Data Management
Perform analysis across multiple source systems, data platforms, applications, and enterprise data assets.
Conduct data profiling, impact analysis, root-cause analysis, gap analysis, and validation activities.
Analyze source system structures, data relationships, and downstream consumption patterns.
Support data lineage documentation and traceability efforts from source systems through reporting, analytics, and operational consumption layers.
Analyze and validate data residing within traditional platforms and cloud-based environments, including Google Cloud Platform (Google Cloud Platform) and BigQuery.
Partner with business stakeholders to define, document, and maintain Critical Data Elements (CDEs), business definitions, and business rules.
Assist in identifying, investigating, and resolving data quality issues and anomalies.
Support metadata management and enterprise data catalog initiatives.
Utilize Alation to document data assets, business definitions, lineage relationships, metadata, and governance information.

Data Supply Chain Analysis, Mapping & Documentation
Analyze and document end-to-end Data Supply Chain processes, integrations, and data movement patterns.
Review existing data sourcing solutions, integration processes, and enterprise data flows to understand current-state architecture and processing.
Analyze and interpret existing Ab Initio graphs, ETL processes, transformation logic, balancing routines, reconciliation processes, and operational workflows.
Review existing source-to-target mappings and technical specifications to understand current data movement and transformation requirements.
Create and maintain detailed source-to-target mapping documentation for enhancement requests, modernization initiatives, and net-new data integrations.
Develop current-state and future-state data flow diagrams, integration documentation, and business process documentation.
Document transformation logic, business rules, control points, data quality controls, balancing requirements, and reconciliation processes.
Conduct impact assessments to identify affected systems, interfaces, reports, data products, analytics assets, Critical Data Elements, and downstream consumers
Ensure mapping and technical documentation remain synchronized with implemented solutions throughout the delivery lifecycle.
Maintain documentation supporting project delivery, testing, operational readiness, governance reviews, regulatory examinations, and audit activities.

Cross-Functional Collaboration & Solution Design
Partner closely with Data Engineers to understand data ingestion, transformation, integration, orchestration, and operational processing requirements.
Collaborate with Data Modelers to evaluate logical and physical data structures and ensure alignment with enterprise data models and standards.
Work alongside Data Architects to understand strategic architecture direction, modernization initiatives, cloud migration efforts, and enterprise integration standards.
Participate in architecture reviews, solution design discussions, and implementation planning sessions.
Serve as a liaison between business stakeholders and technical teams to ensure a shared understanding of requirements, priorities, dependencies, and expected outcomes.
Support design decisions through fact-based business and data analysis.
Identify risks, assumptions, dependencies, and opportunities early in the project lifecycle.
Evaluate impacts associated with modernizing legacy processes and transitioning data assets to cloud-based platforms and analytical ecosystems.

Project Intake, Planning & Delivery Support
Support EDAS demand management, project intake, prioritization, and planning processes.
Evaluate new requests for business value, complexity, dependencies, data impacts, and implementation readiness.
Assist with high-level sizing, planning assumptions, and Business Planning Estimates (BPEs).
Identify impacted systems, integration points, data domains, Critical Data Elements, and downstream consumers during project intake activities.
Support Agile delivery teams through requirements clarification, testing support, and implementation readiness activities.
Assist with User Acceptance Testing (UAT), data validation, defect triage, and business verification activities.
Track risks, issues, dependencies, action items, and key project decisions.

Data Governance, Risk & Compliance Support
Support enterprise Data Governance, Data Management, and Data Quality initiatives.
Partner with Data Owners, Data Stewards, Governance teams, and Risk partners to improve data management maturity.
Support activities related to Critical Data Elements (CDEs), Data Ownership, Data Stewardship, Data Quality, Data Lineage, and Metadata Management.
Assist with CDE certification, business rule documentation, lineage documentation, issue remediation, and governance reviews.
Support regulatory, audit, compliance, and risk management initiatives requiring data analysis, traceability, and documentation.
Promote adherence to enterprise data standards, governance requirements, and best practices.
Support Alation adoption and documentation efforts to improve data discoverability, transparency, and trust across the enterprise.

Leadership & Influence Expectations
Operate independently with minimal supervision across multiple concurrent initiatives
Serve as a trusted advisor to business stakeholders and technology partners regarding data sourcing strategies, governance considerations, integration approaches, and implementation impacts.
Lead complex discovery, impact assessment, data lineage, and data requirements efforts spanning multiple systems and business domains.
Drive alignment across Business SMEs, Data Owners, Data Stewards, Data Engineers, Data Modelers, Data Architects, Governance teams, and project stakeholders.
Influence decision-making through fact-based analysis, risk identification, and actionable recommendations.
Mentor and provide guidance to less experienced analysts when appropriate.
Identify opportunities to improve Data Supply Chain processes, governance practices, documentation standards, and delivery effectiveness.
Champion best practices related to data governance, Critical Data Elements (CDEs), metadata management, lineage, and data quality.

Required Qualifications
Education
Bachelor's degree in business, Information Systems, Computer Science, Analytics, Data Management, Finance, or a related discipline.
Equivalent combination of education and experience may be considered.

Experience
8+ years of experience in Business Analysis, Data Analysis, Data Management, Data Integration, Data Governance, Data Warehousing, or related disciplines.
Demonstrated experience supporting enterprise-scale data, analytics, integration, modernization, or regulatory initiatives.
Experience gathering, documenting, and validating enterprise data requirements across multiple business domains.
Experience creating source-to-target mappings, transformation specifications, business rule documentation, and data flow documentation.
Experience performing data lineage analysis, impact assessments, data profiling, and data validation activities.
Experience working directly with business stakeholders, Data Engineers, Data Modelers, Data Architects, and other technical delivery teams.
Strong SQL and analytical problem-solving skills.
Experience operating within large, complex enterprise environments.
Ability to lead discovery efforts and work independently with minimal supervision.

Technical Skills
Advanced SQL and data analysis capabilities.
Strong understanding of relational databases, enterprise data architecture, and data warehousing concepts.
Experience documenting data sourcing requirements, transformation logic, business rules, and data quality controls.
Experience performing data profiling, impact assessments, lineage analysis, and validation activities.
Familiarity with metadata management and data governance concepts.
Experience with Jira and Confluence.
Strong analytical, communication, facilitation, and documentation skills.

Preferred Qualifications
10+ years of experience supporting enterprise data management, data governance, data integration, or analytics initiatives.
Financial Services or Banking industry experience.
Experience supporting Enterprise Data Governance, Data Quality, Data Risk, or Regulatory Data programs.
Working knowledge of Critical Data Elements (CDEs), Data Ownership, Data Stewardship, Data Lineage, and Metadata Management.
Experience utilizing Alation Data Catalog.
Experience reviewing and documenting Ab Initio data flows, integrations, and source-to-target mappings.
Experience with Google Cloud Platform (Google Cloud Platform) and BigQuery.
Experience supporting cloud migration, modernization, or enterprise data transformation initiatives.
Agile delivery experience.

What Success Looks Like

• Improve the quality and completeness of project intake requests.
• Accelerate project planning through effective impact analysis and data requirements management.
• Understand and document complex Data Supply Chain processes, integrations, and dependencies.
• Analyze existing Ab Initio data flows and mapping documentation to support enhancement and modernization initiatives.
• Develop implementation-ready source-to-target mappings and future-state data flow documentation.
• Partner effectively with Business SMEs, Data Engineers, Data Modelers, Data Architects, Data Owners, and Governance teams.
• Support Critical Data Element (CDE) identification, documentation, governance, stewardship, and certification activities.
• Utilize Alation to improve metadata quality, lineage visibility, and documentation maturity.
• Identify risks, dependencies, and data quality concerns early in the delivery lifecycle.
• Enable informed decision-making through fact-based analysis and recommendations.
• Improve the consistency, quality, and maintainability of EDAS documentation, data assets, and governance processes.