Apache Spark/Trino Support Engineer

2 days ago

Bengaluru, Karnataka, India Bharat Head Hunters Full time

Job Title : Support Engineer Apache Spark with Druid/Trino (L1 Support)

Location : Bangalore, Chennai, Hyderabad

Experience : 4 to 11 Years

Employment Type : Full-time

We are seeking a dedicated Support Engineer with strong experience in Apache Spark along with Druid or Trino to provide Level 1 production support in a high-performance big data environment. In this role, the engineer will be responsible for monitoring Spark jobs, supervising data ingestion pipelines in Druid, and supporting query execution through Trino.

- The engineer will manage incidents raised during production, investigate job failures, carry out initial root cause analysis, and perform first-level troubleshooting to restore services quickly.

- Any issues beyond the scope of L1 will be documented in detail and escalated promptly to L2 and L3 teams to ensure seamless resolution.

- The Support Engineer will be expected to work extensively with enterprise monitoring and alerting tools such as Grafana, Prometheus, or Splunk to identify system performance bottlenecks and failures in real time.

- Job orchestration and scheduling tools like Autosys, Airflow, or Oozie will form part of the daily operations.

- The engineer will maintain shift-based monitoring, ensuring round-the-clock availability of the platform, while also preparing and updating knowledge base articles and standard operating procedures for recurring issues. Attention to detail and strict adherence to SLAs will be critical in maintaining production stability and delivering high-quality support.

The ideal candidate should bring a solid background in production support, application support, or big data support, with proven expertise in Apache Spark and either Druid or Trino.

- Hands-on knowledge of incident management platforms such as ServiceNow, JIRA, or Remedy is required, along with strong working skills in Linux, SQL, and basic shell scripting to diagnose and fix operational issues.

- Additional exposure to other big data tools such as Hive, Hadoop, or Kafka, and knowledge of cloud environments like AWS, Azure, or GCP will be considered advantageous.

- Strong communication and interpersonal skills are essential, as the engineer will be required to collaborate with cross-functional teams, provide timely updates on incident resolution, and interact effectively with business stakeholders.

(ref:hirist.tech)

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