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Key Responsibilities:
- Provide L2/L3 production support for big data platforms, ensuring high availability and reliability of clusters and data pipelines.
- Monitor big data jobs, workflows, and resource utilization; proactively identify and resolve performance bottlenecks and failures.
- Perform incident management, including impact analysis, root-cause investigation, and timely resolution with clear communication to stakeholders.
- Manage and support batch and streaming data ingestion processes, validating data quality and integrity across environments.
- Collaborate with data engineering teams to deploy, validate, and stabilize new big data solutions and enhancements.
- Create and maintain runbooks, standard operating procedures, and knowledge base articles for recurring issues and operational tasks.
- Participate in on-call rotations, change management, and release activities for big data components and jobs.
- Automate routine support activities and monitoring tasks to improve efficiency and reduce manual interventions.
- Track and report key support metrics, providing recommendations for continuous improvement of platform reliability and support processes. Minimum Qualifications:
- B.Tech degree in Computer Science, Information Technology, or a related engineering discipline.
- 3–5 years of hands-on experience in big data environments, focusing on platform or application support.
- Strong understanding of big data concepts such as distributed processing, cluster management, and data pipelines.
- Proven experience in monitoring, troubleshooting, and resolving issues in big data jobs and workflows in production environments.
- Ability to analyze logs, identify root causes, and implement stable fixes or workarounds for recurring incidents.
- Solid understanding of ITIL-aligned support practices, including incident, problem, and change management in a production setup. Good to have skills: Linux administration, Shell scripting, SQL, Mon