Data Project Manager
Job Description & 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, and deployment).
- Estimate timelines, budget, and resource requirements.
- Identify data sources, ownership, and access requirements early.
2. Stakeholder Management
- Act as the primary liaison between business teams, data engineers, analysts, data scientists, and leadership.
- Gather and translate business requirements into technical specifications.
- Manage expectations around data quality, timelines, and scope changes.
- Report progress, risks, and blockers to sponsors and steering committees.
3. Team Coordination
- Assign tasks across data engineers, analysts, DBAs, QA testers, and data scientists.
- Facilitate stand-ups, sprint planning, and retrospectives (often Agile/Scrum or Kanban).
- Resolve cross-functional dependencies (e.g., IT infrastructure, security, and compliance teams).
4. Data Governance & Quality Oversight
- Ensure data quality standards, validation rules, and cleansing processes are followed.
- Coordinate with governance and compliance teams on privacy, security, and regulatory requirements.
- Track data lineage and documentation requirements.
5. Risk & Issue Management
- Identify risks specific to data projects, including data quality issues, schema changes, integration failures, and scalability concerns.
- Maintain a risk register and mitigation plans.
- Escalate blockers (e.g., missing access, vendor delays, and infrastructure limitations).
6. P&L, Budget Tracking & Resource Management
- Track costs.
- Manage vendor and contractor relationships if external data tools or consultants are used.
7. Quality Assurance & Testing Oversight
- Ensure testing plans cover data validation, transformation logic, and end-to-end pipeline testing.
- Coordinate UAT (User Acceptance Testing) with business stakeholders.
8. Documentation & Reporting
- Maintain project documentation, including requirements, data dictionaries, architecture diagrams, and status reports.
- Ensure knowledge transfer and handover documentation for ongoing maintenance.
9. Deployment & Change Management
- Oversee rollout and migration plans, including rollback strategies.
- Manage change requests and their impact on scope and timelines.
- Support user training and adoption post-launch.
10. Post-Project Evaluation
- Conduct post-mortems and retrospectives to capture lessons learned.
- Measure project outcomes against KPIs (data accuracy, system performance, and business impact).
Required Skills
- Technical fluency in Cloud architectures (GCP/AWS), PySpark/Scala data pipelines, metadata management, data warehousing, and scheduling platforms.
- Ability to communicate effectively between technical and business teams and make informed trade-off decisions.
Thanks,
Saghana Sithara
Business Manager, Recruitment| Quess Selection & Services, Singapore
EA License Number: 23C2060 Registration ID is R1550224
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“This is in partnership with the Employment and Employability Institute Pte Ltd (“e2i”).
e2i is the empowering network for workers and employers seeking employment and employability solutions. e2i serves as a bridge between workers and employers, connecting with workers to offer job security through job-matching, career guidance and skills upgrading services, and partnering employers to address their manpower needs through recruitment, training, and job redesign solutions. e2i is a tripartite initiative of the National Trades Union Congress set up to support nation-wide manpower and skills upgrading initiatives. By applying for this role, you consent to Quesscorp Singapore’s PDPA and e2i’s PDPA.”