Description :
Vopais is hiring a talented SME Application Support Engineer (Databricks) to join our Mumbai office for 247 rotational operations. We seek driven professionals with 6-8 years of experience in Big Data and Databricks to optimize solutions for data platform reliability and performance.
Key Responsibilities :
- Be the first escalation point for 247 monitoring and assurance of Databricks clusters, jobs, workflows, repos, and critical data pipelines.
- Troubleshoot and analyze SME-level issues including cluster failures, auto-scaling, job failures in PySpark / Scala / Spark SQL / Delta Live Tables, and workspace availability.
- Partner with application development owners to remediate pipeline and job failures.
- Lead and participate in Sev1 / Sev2 incident resolutions, preparing RCA documentation.
- Implement workspace governance, including user access (RBAC), cluster policy enforcement, and data security best practices.
- Ensure platform compliance with audit and regulatory requirements.
- Build and maintain custom dashboards / logging for job performance, failure analytics, and cluster utilization.
- Maintain SOPs, runbooks, and architecture documentation provided by Data Engineering / Platform Engineering.
- Identify recurring issues and escalate to L3 / Platform Engineering for resolution.
- Support debugging of complex Spark issues, including memory management (OOM errors), long garbage collection cycles, and overall cluster health.
Must-Have Skills :
Proven experience in Big Data cloud data platform support, with SME expertise on Databricks platform (clusters, jobs, repos, MLflow, warehouse).Strong hands-on skills in UNIX, SQL, and Shell Scripting.Advanced Spark job debugging, Spark UI, and analytics.Robust experience with CICD pipelines (Azure DevOps), Apache Spark, and Azure Cloud.Ability to work rotational shifts including nights and weekends.Qualifications :
B.E / B.Tech / MCA in Computer Science, IT, or equivalent.
Compensation : Up to 30 LPA
Location : Navi Mumbai (RCP)
Joiners : Immediate only
(ref : hirist.tech)