Project Manager - ETL / Data Engineering

Job Title - Project Manager

Experience: 1215 Years

Domain: Data Engineering / Technology

Role Overview:

We are looking for an experienced Project Manager with 12–15 years of experience in managing complex technology and data engineering projects. The candidate should have strong expertise in Agile methodologies and Scaled Agile Framework (SAFe) and proven experience leading large, cross-functional teams in an enterprise environment.

Experience with Databricks is preferred. However, if the candidate does not have Databricks experience, strong experience managing ETL/Data Engineering projects is mandatory.

Key Responsibilities:

• Lead end-to-end delivery of large and complex technology/data engineering projects.
• Manage projects using Agile, Scrum, Kanban, and Scaled Agile (SAFe) methodologies.
• Drive Agile ceremonies including Sprint Planning, Daily Stand-ups, Sprint Reviews, Retrospectives, and PI Planning.
• Coordinate delivery across multiple Agile teams and manage cross-team dependencies.
• Partner with Product Owners, Scrum Masters, Data Engineers, Architects, QA teams, and business stakeholders.
• Own project planning, timelines, milestones, resource allocation, risks, issues, dependencies, and overall delivery governance.
• Proactively identify and mitigate project risks and resolve delivery impediments.
• Manage stakeholder expectations and provide regular project status updates to senior leadership.
• Drive delivery in line with organizational Agile/SAFe processes, governance, quality standards, and compliance requirements.
• Monitor project progress, capacity, resource utilization, and delivery metrics.
• Manage geographically distributed and cross-functional teams effectively.
• Drive continuous improvement and promote Agile best practices across teams.
• Work closely with technical teams to understand data pipelines, ETL/ELT processes, integrations, data platforms, and data architecture.
• Ensure timely delivery of project milestones while maintaining quality and scope.

Must-Have Skills & Experience:

• 12–15 years of overall experience in IT/Technology Project Management.
• Strong experience managing Agile projects in an enterprise environment.
• Strong hands-on experience with Scaled Agile / SAFe.
• Proven experience managing multiple Agile teams and complex cross-team dependencies.
• Strong understanding of Scrum, Kanban, Agile delivery practices, and PI Planning.
• ETL/Data Engineering project experience is mandatory for candidates without Databricks experience.
• Good understanding of ETL/ELT, data pipelines, data integration, data warehouses, and data platforms.
• Strong experience in project planning, risk management, dependency management, stakeholder management, and delivery governance.
• Experience working with senior business and technology stakeholders.
• Excellent communication, leadership, negotiation, and problem-solving skills.
• Ability to manage complex projects with multiple stakeholders, teams, and dependencies.

Preferred Skills:

• Databricks experience is highly preferred.
• Experience with modern cloud data platforms and data engineering environments.
• Exposure to Azure, AWS, or GCP.
• Experience managing Data Lake, Data Warehouse, Analytics, or Big Data projects.
• Experience with tools such as Jira, Confluence, Azure DevOps, or similar Agile delivery tools.
• SAFe certification such as SAFe Agilist, SAFe Scrum Master, or SAFe Release Train Engineer is a plus.
• PMP / PMI-ACP or equivalent project management certification is a plus.

Desired Candidate:

The ideal candidate should be a senior, delivery-focused Project Manager with 12–15 years of experience who can effectively manage large-scale Agile programs and bridge the gap between business and technical teams.

They should have strong knowledge of Agile and SAFe, excellent stakeholder management skills, and experience delivering data engineering/ETL projects.