Job

location:
Whitefield,Bangalore Work Mode: Hybrid(3 days/office)

Job Description
We are looking for a Big Data Support Engineer with hands-on experience in production support and troubleshooting of Apache Spark applications running on Kubernetes. The candidate will be responsible for monitoring applications, analyzing logs, resolving production incidents, troubleshooting job failures, and maintaining application stability. The ideal candidate should have experience with Spark, Kubernetes, Hive, monitoring tools such as Splunk and Grafana, and IT incident management processes using Jira.

Key Responsibilities
- Provide L1/L2 production support for Apache Spark applications and Big Data platforms.
- Monitor application health, scheduled jobs, system alerts, resource utilization, and performance.
- Troubleshoot Spark job failures, executor issues, memory errors, application logs, and performance bottlenecks.
- Troubleshoot Kubernetes-related issues, including pod failures, container errors, resource allocation, and application deployment issues.
- Support Apache Hive and investigate query failures and related application issues.
- Use monitoring and log analysis tools such as Splunk, Grafana, and Recent Relic to identify errors, investigate incidents, and monitor application performance.
- Perform log analysis, routine health checks, service restarts, and basic configuration validation.
- Create, update, track, and resolve incident and problem tickets using Jira and follow established incident management processes.
- Ensure timely incident resolution and escalation in accordance with defined SLAs.
- Coordinate with L3 support, infrastructure,



application, and other technical teams to resolve complex issues.
- Document troubleshooting steps, recurring issues, root-cause findings, and resolution procedures. Mandatory Technical Skills 1. Apache Spark:Hands-on experience troubleshooting Spark job failures, executor errors, memory issues, logs, and performance problems. 2. Kubernetes (K8s): Practical troubleshooting experience involving pod failures, container logs, resource allocation, and application-related issues. 3. Apache Hive:Working knowledge of Hive and experience supporting or troubleshooting Hive-related issues. 4. Monitoring and Log Analysis: Experience with tools such as Splunk, Grafana, and/or New Relic. Candidates must have practical experience investigating alerts, analyzing logs, and troubleshooting production issues. Splunk troubleshooting experience is specifically required. 5. Jira and ITSM Processes: Experience handling incidents, updating tickets, managing escalations, tracking resolution, and following incident/problem management processes. 6. Production Support: Experience in L1/L2 application support, incident resolution, SLA management, and production issue troubleshooting. 7. Linux/Unix: Basic command-line knowledge and the ability to analyze application logs and investigate issues. Candidate Expectations
- Strong troubleshooting and analytical skills.
- Ability to investigate issues independently and identify the likely root cause.
- Good communication and coordination skills for working with L3 and infrastructure teams.
- Willingness to work in a production support environment, including rotational shifts if required.

📌 Big Data Support Engineer (Bengaluru)
🏢 ACL Digital
📍 Bengaluru