Gsinsight Consulting Services Chennai
Engineering Manager
Skills
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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