Senior Data Management Business Analyst - Ab Initio Analysis exp - Onsite - Brooklyn, OH - Direct Client

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.

• 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.

• 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.

• 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.

• 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.

• 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.