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Engineering Manager

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Hybrid

Engineering Manager

Gsinsight Consulting Services Chennai

Engineering Manager

Skills

Google Cloud PlatformData EngineeringAWSJiraConfluenceAzure

2 months ago

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Important information


Contract type:

Permanent

Salary:

₹1,500,000 – ₹3,000,000 / year

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

3 September 2026

What they need


This is initially C2H for 6 months, then will be taken into direct payroll

Responsibilities

  • Lead the design and implementation of large-scale data engineering projects, including

data lakes and data pipelines on cloud platforms like AWS, Azure, or GCP.

  • Drive the pre-sales process by engaging with clients, understanding requirements, and

developing technical proposals and proof of concepts (PoCs).

  • Manage end-to-end programme delivery across all sprints: sprint planning, backlog prioritisation, velocity tracking, and milestone governance for a distributed team of data engineers, leads, and analysts.
  • Act as the primary escalation point for blockers and dependencies; coordinate environment readiness and release scheduling with the DevOps Engineer.
  • Drive stakeholder communication, change-request management, and progress reporting.
  • Champion continuous improvement Agile best practices, documentation quality, and a high-performance delivery culture across the offshore-onshore team.

Required Skills

  • Proven experience managing distributed data engineering teams in an Agile / Scrum framework using JIRA and Confluence.
  • Sufficient GCP data engineering knowledge to assess technical risks, facilitate architecture discussions, and manage delivery trade-offs.
  • Strong stakeholder management and executive reporting skills; experience managing client expectations in fixed-scope engagements.
  • Servant-leadership mindset with expertise in offshore / onshore team coordination, time-zone management, and knowledge transfer.
  • Excellent communication skills to effectively interact with stakeholders, clients, and
  • technical teams.
  • 810 years of professional experience, including delivery and engineering management of data engineering or data platform programs, with hands-on involvement in at least one data lake implementation.

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