Project Management:
• Min 15+ years of experience
• Experience managing Data Governance and Master Data Management projects
• BFSI experience highly preferred
• Informatica product implementation is highly preferred
Planning, execution, and successful delivery of data engineering projects
Project initiation and planning: Define project scope, objectives, timelines, budget, resources, and risks.
Resource management: Allocate, manage, and track the performance of the data engineering team.
Communication and collaboration: Facilitate communication between stakeholders, including data engineers, data scientists, business analysts, and executives.
Risk management: Identify, assess, and mitigate project risks proactively.
Issue resolution: Address project challenges and issues promptly and effectively.
Monitoring and reporting: Track project progress, measure performance against targets, and report findings to stakeholders regularly.
Technical Expertise:
Understanding of data engineering principles and practices: While not requiring in-depth coding expertise, possessing a strong understanding of data pipelines, data storage solutions, data quality concepts, and data security is crucial.
Familiarity with data engineering tools and technologies: This may include knowledge of ETL/ELT tools, cloud platforms (AWS, Azure, GCP), data warehousing solutions, and data governance frameworks.
Additional Skills:
Problem-solving and critical thinking
Analytical skills
Organizational skills
Strong interpersonal and communication skills
Overall, a Data Engineering Project Manager requires a blend of technical knowledge, project management expertise, and strong communication skills to ensure the successful delivery of data-driven projects that unlock the power of data for their organization.
Notice period should not more than 30 days.
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