Project Manager-Data Engineering

5 days ago

India InOrg Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Job Title: Technical Project Manager – Data Engineering (Databricks Practice)

Company:

Type: Full-time

Experience Level: Mid to Senior

Key Responsibilities

  • Lead and manage end-to-end delivery of data engineering projects, ensuring timelines, budgets, and quality standards are met.

  • Coordinate between data engineers, solution architects, business stakeholders, and clients to align project objectives.

  • Track and manage project plans, risks, dependencies, and progress through agile/scrum methodologies.

  • Ensure adherence to data engineering best practices across design, build, and deployment.

  • Support solution design discussions for data pipelines, data lake/lakehouse, and cloud data platforms.

  • Drive continuous improvement by implementing accelerators, reusable assets, and governance frameworks.

  • Partner with the Technology Steering Committee to stay updated on emerging trends, tools, and practices.

  • Prepare and deliver regular project status updates, executive reports, and stakeholder communication.

Requirements

Experience: 5+ years in project/program management with strong exposure to data engineering or analytics projects.

Technical Knowledge (preferred, not mandatory):

  • Familiarity with Databricks, Apache Spark, or other big data frameworks.

  • Understanding of cloud platforms (AWS, Azure, or GCP).

  • Exposure to data lakes, data warehouses, and lakehouse concepts.

  • Knowledge of CI/CD pipelines, version control, and agile delivery practices.

Soft Skills:

  • Excellent leadership, communication, and stakeholder management skills.

  • Strong problem-solving and conflict-resolution abilities.

  • Proven ability to manage distributed, cross-functional teams.

Nice to Have

  • Prior experience managing projects with Databricks or modern data platforms.

  • Project management certifications (PMP, CSM, PRINCE2, or equivalent).

  • Familiarity with monitoring and observability tools (Datadog, Prometheus, etc.).

  • Exposure to ML or advanced analytics projects.

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