Our client, a Banking company, is looking for a Senior Project Manager for their Brooklyn, OH location.
Responsibilities:- 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 (GCP) and BigQuery is beneficial
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 (GCP) 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.
- 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.
Requirements:- 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
- 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.
- 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
- 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 (GCP) and BigQuery.
- Experience supporting cloud migration, modernization, or enterprise data transformation initiatives.
- Agile delivery experience.
Why Should You Apply?