Data Project Manager(Clients IBM, DBS)

JD : DATA Project Manager

• Sr PM – 9+ years of experience

Key Responsibilities

1. Planning & Scoping Define project objectives,deliverables, and success criteria in collaboration with stakeholders Break down work into phases(requirements, data sourcing, modeling, ETL/ELT, validation, deployment) Estimate timelines, budget,and resource needs Identify data sources,ownership, and access requirements early
2. Stakeholder Management Act as the primary liaisonbetween business teams, data engineers, analysts, data scientists, andleadership Gather and translate businessrequirements into technical specifications Manage expectations around data quality, timelines, and scope changes Report progress, risks, andblockers to sponsors and steering committees
3. Team Coordination Assign tasks across dataengineers, analysts, DBAs, QA/testers, and data scientists Facilitate standups, sprintplanning, and retrospectives (often Agile/Scrum or Kanban) Resolve cross-functionaldependencies (e.g., IT infrastructure, security, compliance teams)
4. Data Governance &Quality Oversight Ensure data qualitystandards, validation rules, and cleansing processes are followed Coordinate withgovernance/compliance teams on privacy, security, and regulatory requirements Track data lineage anddocumentation requirements
5. Risk & IssueManagement Identify risks specific todata projects: data quality issues, schema changes, integration failures,scalability concerns Maintain a risk register andmitigation plans Escalate blockers (e.g.,missing access, vendor delays, infrastructure limits)
6. P&L - Budgettracking & Resource Management Track costs Manage vendor/contractorrelationships if external data tools or consultants are used
7. Quality Assurance &Testing Oversight Ensure testing plans coverdata validation, transformation logic, and end-to-end pipeline testing Coordinate UAT (useracceptance testing) with business stakeholders
8. Documentation &Reporting Maintain projectdocumentation: requirements, data dictionaries, architecture diagrams, statusreports Ensure knowledge transfer andhandover documentation for ongoing maintenance
9. Deployment & ChangeManagement Oversee rollout/migration plans, including rollback strategies Manage change requests and their impact on scope/timeline Support user training and adoption post-launch
10. Post-ProjectEvaluation Conductpost-mortems/retrospectives to capture lessons learned Measure project outcomesagainst KPIs (data accuracy, system performance, business impact) Required Skills Have technical fluency to understand Cloud architecture(GCP/AWS), Pyspark/Scala data pipelines, Metadatamanagement, Datawarehousing, Scheduling To communicate effectivelybetween technical and business teams and to make informed tradeoff decisions.