Senior Data Management Business Analyst

Overview Client•Brooklyn, OH

5h•Onsite

About The Position

Client is seeking a Senior Data Management Business Analyst to support enterprise data initiatives, modernization efforts, data governance programs, and Data Supply Chain delivery. This role will translate business needs into actionable data requirements, analyze complex data environments, document current- and future-state data flows, and coordinate delivery across business, data, architecture, governance, and engineering teams.

Requirements

Bachelor's degree in Business, Information Systems, Computer Science, Analytics, Data Management, Finance, or a related discipline, or an equivalent combination of education and experience.
8+ years of experience in business analysis, data analysis, data management, data integration, data governance, data warehousing, or related disciplines.
Experience supporting enterprise-scale data, analytics, integration, modernization, or regulatory initiatives.
Experience gathering, documenting, and validating enterprise data requirements across multiple business domains.
Advanced SQL and data analysis capabilities.
Experience creating source-to-target mappings, transformation specifications, business rules, and data flow documentation.
Experience performing data lineage analysis, impact assessments, data profiling, and data validation.
Strong understanding of relational databases, enterprise data architecture, and data warehousing concepts.
Experience documenting data sourcing requirements, transformation logic, and data quality controls.
Familiarity with metadata management and data governance concepts.
Experience working with business stakeholders, Data Engineers, Data Modelers, Data Architects, and technical delivery teams.
Experience with Jira and Confluence.
Ability to lead discovery efforts and operate independently across multiple concurrent initiatives.

Nice To Haves

10+ years of enterprise data management, data governance, data integration, or analytics experience.
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, Data Ownership, Data Stewardship, Data Lineage, and Metadata Management.
Experience using Alation Data Catalog.
Experience reviewing and documenting Ab Initio data flows, integrations, and source-to-target mappings.
Experience with Google Cloud Platform and BigQuery.
Experience supporting cloud migration, modernization, or enterprise data transformation initiatives.
Agile delivery experience.

Responsibilities

Lead stakeholder discovery sessions, workshops, interviews, and data requirements discussions.
Gather, analyze, document, and validate data sourcing requirements, business rules, Critical Data Elements, metadata requirements, data quality expectations, and lineage considerations.
Translate business needs into source-to-target mappings, transformation logic, data quality controls, and consumption requirements.
Perform data profiling, impact analysis, root-cause analysis, gap analysis, and data validation.
Analyze source systems, data relationships, integrations, ETL processes, and downstream consumption patterns.
Document end-to-end data lineage and traceability across reporting, analytics, governance, and operational platforms.
Analyze existing Ab Initio graphs, transformation logic, balancing routines, reconciliation processes, and operational workflows.
Create and maintain current- and future-state data flow diagrams, source-to-target mappings, integration documentation, and business process documentation.
Partner with Data Engineers, Data Modelers, Data Architects, Product Owners, Data Owners, Data Stewards, and governance teams.
Support metadata management and enterprise data catalog activities using Alation.
Participate in architecture reviews, solution design, implementation planning, project intake, prioritization, and Business Planning Estimates.
Support Agile delivery through requirements clarification, UAT, data validation, defect triage, and implementation readiness.
Support data governance, data quality, data risk, regulatory, compliance, and audit initiatives.
Identify and communicate project risks, assumptions, dependencies, impacts, and recommendations.
Lead complex data discovery, impact assessment, lineage, and requirements efforts across multiple systems and business domains.
Mentor less experienced analysts and promote data management and governance best practices.