
Data Engineering Manager
- Mumbai, Maharashtra
- Permanent
- Full-time
- Data Engineering Lifecycle: Lead research, proof of concept, architecture, development, testing, deployment, and ongoing maintenance of data solutions
- Data Solutions: Design and implement modular, flexible, secure, and reliable data systems that scale with business needs
- Instrumentation and Monitoring: Integrate pipeline observability to detect and resolve issues proactively
- Troubleshooting and Optimization: Develop tools and processes to debug, optimize, and maintain production systems
- Tech Debt Reduction: Identify and address legacy inefficiencies to improve performance and maintainability
- Debugging and Troubleshooting: Quickly diagnose and resolve unknown issues across complex systems
- Documentation and Governance: Maintain clear documentation of data models, transformations, and pipelines to ensure security and governance compliance
- Cloud Expertise: Leverage advanced skills in AWS and EKS to build, deploy, and scale cloud-native data platforms
- Cross-Functional Support: Collaborate with analytics, application development, and business teams to enable data-driven solutions
- Team Leadership: Lead and mentor engineering teams to ensure operational efficiency and innovation
- Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
- SG 27 and SG 28 can apply
- SG 27 will move to SG 28; SG 28 will move laterally
- Performance rating in the last common review cycle of "Meets Expectations" or higher
- Not be on any active CAP (Corrective Action Plan) or active disciplinary action
- Time in Role Guidelines:
- Should have been in your current position for a minimum of 12 months, if you have not met the recommended minimum time in role, discuss your career interest with your manager and gain alignment prior to applying. And share the alignment email with respective recruiter while applying
- Bachelor’s degree in Computer Science or related field
- 5+ years of experience in data engineering or related roles
- Proven experience designing and deploying scalable, secure, high-quality data solutions
- Solid expertise in full Data Engineering lifecycle (research to maintenance)
- Advanced AWS and EKS knowledge
- Proficient in CI/CD, IaC, and addressing tech debt
- Proven skilled in monitoring and instrumentation of data pipelines
- Proven advanced troubleshooting and performance optimization abilities
- Proven ownership mindset with ability to manage multiple components
- Proven effective cross-functional collaborator (DS, SMEs, and external teams).
- Proven exceptional debugging and problem-solving skills
- Proven solid individual contributor with a team-first approach