Senior Project Manager - Data Management

ApTask; Brooklyn (OH); On-site; USD 110,000 - 150,000; Full time

Job summary

ApTask is seeking a Senior Data Management Business Analyst to support strategic data initiatives, governance programs, and Data Supply Chain delivery. You will partner with stakeholders, document data requirements, and translate business needs into actionable data specifications, mappings, and governance artefacts.

Strong collaboration with data engineers, modelers, and architects is essential. The role emphasizes data lineage, metadata management, and leveraging GCP/BigQuery capabilities to

Qualifications

• Bachelor's degree required or equivalent experience.
• 8+ years in BA, data analysis, governance, or data management.
• Experience documenting data requirements, mappings, and data flows.

Responsibilities

• Partner with stakeholders to understand objectives and data needs.
• Elicit and validate enterprise data requirements, CDEs, and lineage.
• Create source-to-target mappings, transformation logic, and data quality controls.
• Develop data flow diagrams and governance documentation.
• Document data supply chain processes and integration patterns.
• Collaborate with data engineers, modelers, and architects on solutions.

Skills

SQL

Data analysis

Stakeholder engagement

Business analysis

Data governance

Education

Bachelor's degree in business, IS, CS, analytics, data management or related

Tools

Jira

Confluence

Ab Initio

BigQuery

GCP

Job description

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 (GCP) 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 (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.

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.
• Commercial Lending, Financial Services or Banking industry experience.

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.