Position: Data Engineering Service ManagerExperience: 6–12 Years

Employment Type: Full-time

Location: Mumbai

Role OverviewWe are looking for an experienced Data Engineering Service Manager to take end-to-end ownership of an OT (Operational Technology) Data Engineering & Analytics Platform.

The role will be responsible for ensuring the availability, reliability, scalability, security, performance, and operational stability of the platform across the complete data journey — from edge/industrial data acquisition through cloud data platforms, ETL/ELT pipelines, data lakes, and analytics services.

This is primarily a service management and platform operations leadership role, with strong technical understanding of Data Engineering. The successful candidate will manage and mentor a team of 4 engineers and work closely with Data Engineering, Cybersecurity, Network, Cloud, Infrastructure and business teams.

The platform includes technologies such as Data Collector, SAS Viya and Google BigQuery, along with data acquisition, streaming, batch processing and analytics capabilities.

Key Responsibilities1.

Data Platform Service

Ownership

- Take end-to-end ownership of the OT Data Engineering & • Analytics platform

.
- Ensure smooth and reliable day-to-day operation of all platform components.
- Define and maintain operational standards, processes, runbooks and SOPs.
- Ensure platform services meet agreed SLA/SLO, availability, performance and data-quality objectives.
- Act as the primary technical/service escalation point for platform-related issues.

2.

Production

Support &

• Operations
- Lead L2/L3 production support for Data Engineering and Analytics platforms.
- Monitor platform health, data pipelines, integrations and data flows.
- Identify and resolve production issues with minimum business impact.
- Coordinate with engineering, cloud, network and infrastructure teams for complex incidents.
- Establish proactive monitoring and observability mechanisms.
- Ensure operational readiness for recent data sources, applications and use cases.

3. Incident, Problem & • Change Management
- Own Incident, Problem and Change Management processes.
- Lead major incident resolution and coordinate cross-functional teams.
- Drive Root Cause Analysis (RCA) and corrective/preventive actions.
- Track recurring incidents and implement measures to prevent recurrence.
- Plan and coordinate platform changes, upgrades and releases.
- Ensure changes are implemented with appropriate risk assessment, testing and rollback plans.

4.



Data Engineering & • Pipeline Management
- Oversee ETL/ELT pipelines across batch and streaming workloads.
- Ensure data pipelines are scalable, reusable, modular and maintainable.
- Standardize ETL/ELT development patterns and templates.
- Monitor pipeline failures, latency, data quality and processing performance.
- Ensure reliable movement of data from industrial/edge sources to cloud and data lake platforms.
- Support onboarding of new sites, assets, applications and data sources.

5. OT / Industrial Data
- Support data acquisition from industrial/OT environments and connected assets.
- Understand IIoT connectivity and industrial data flows.
- Work with time-series and machine/asset-generated data.
- Coordinate with OT, Network, Cybersecurity and Infrastructure teams to establish secure connectivity.
- Ensure reliable and secure transmission of data from edge environments to cloud platforms.

6. Cloud, Data Lake & • Analytics Platforms
- Manage and support cloud-based data engineering and analytics services.
- Work with technologies such as Google BigQuery, SAS Viya and Data Collector.
- Oversee data lake and analytical workloads.
- Ensure appropriate capacity, performance and cost management.
- Support platform scaling based on business and data-volume requirements.

7. Security & • Compliance
- Work closely with Cybersecurity and Network teams to ensure secure platform connectivity.
- Ensure appropriate access controls, authentication and authorization mechanisms.
- Support security patching, vulnerability remediation and platform hardening.
- Ensure operational processes comply with organizational security and compliance requirements.

8.

Disaster

Recovery &

• Business Continuity
- Develop, maintain and test Disaster Recovery (DR) procedures.
- Ensure appropriate backup, recovery and failover mechanisms.
- Conduct periodic DR exercises and identify gaps.
- Maintain documentation and recovery runbooks.

9.

Technology Lifecycle

Management
- Own lifecycle management of platform components and use cases.
- Identify outdated, unsupported or obsolete technologies.
- Develop modernization and migration plans.
- Coordinate technology upgrades,



replacements and retirements.
- Ensure the platform remains scalable, secure and aligned with technology standards.

10. Team Leadership
- Lead and mentor a team of 4 Data Engineering/Platform Engineers.
- Allocate tasks and manage priorities based on business requirements.
- Conduct technical mentoring and knowledge-sharing sessions.
- Establish operational best practices within the team.
- Monitor team performance and ensure timely resolution of production issues.
- Build a strong culture of ownership, collaboration and continuous improvement.

Required Technical SkillsData Engineering

- Strong understanding of Data Engineering concepts and data platforms.
- Hands-on/solid understanding of ETL/ELT pipelines.
- Experience with batch and streaming data processing.
- Experience working with Data Lakes.
- Understanding of data quality, data lineage and pipeline monitoring.

OT / IIoT

- Experience with Industrial/OT data acquisition.
- Understanding of IIoT connectivity.
- Experience working with time-series data.
- Understanding of edge-to-cloud data flows is preferred.

Cloud & Analytics

- Experience with cloud-based data platforms.
- Google BigQuery / GCP experience is highly desirable.
- Experience with SAS Viya is an advantage.
- Experience with other cloud platforms such as AWS/Azure can also be considered.

Operations & Service Management

- Strong experience in production support and platform operations.
- Incident, Problem and Change Management.
- Major Incident Management.
- Root Cause Analysis.
- SLA/SLO management.
- L2/L3 support.
- Monitoring and observability.
- Disaster Recovery and business continuity.
- Configuration, patch and upgrade management.
- ITIL knowledge/certification is preferred.

Required Soft Skills
- Strong leadership and team-management skills.
- Excellent problem-solving and analytical abilities.
- Strong communication and stakeholder-management skills.
- Ability to work across technical and business teams.
- Strong ownership and accountability.
- Ability to handle critical production incidents under pressure.
- Good documentation and process-management skills.
- Ability to drive modernization and continuous improvement initiatives.

Preferred Industry ExperienceCandidates with experience in the following domains will be preferred:
- Industrial / Manufacturing
- Oil & Gas
- Energy & Utilities
- Automotive
- Industrial Automation
- Engineering & Manufacturing
- Industrial IoT / IIoT
- Operational Technology (OT)

📌 Service Manager Data Engineering (Mumbai)
🏢 3:33
📍 Mumbai