Senior Designated Support Engineer

Databricks Databricks · Data AI · India · Engineering

This role is for a Senior Designated Support Engineer at Databricks, focusing on providing high-touch specialized support and technical solutions for large enterprise customers. The engineer will leverage expertise in Spark, ML, and AI runtime capabilities to troubleshoot complex issues, build POCs, develop playbooks, and train customers on Databricks features. The role requires strong technical skills in big data, Spark, data engineering, cloud platforms, and customer-facing experience.

What you'd actually do

  1. Perform advanced Troubleshooting and Root Cause Analysis to resolve performance and reliability issues in Spark, SQL, Delta, Streaming, and Databricks runtime features using tools like Spark UI metrics, Mosaic AI Model Service, DAGs, and event logs.
  2. Discover requirements for continuous monitoring to detect early performance issues working with R&D and NOC teams to optimize the DNB customer environments.
  3. Build Rapid POCs, Test/Deploy/Monitor the solutions built by Databricks Engineering to address customer challenges and showcase advanced Spark/ML/AI runtime capabilities aligned with their business goals.
  4. Develop comprehensive playbooks and maintain a knowledge base of common issues and solutions for Spark, ML, and AI workflows.
  5. Train customer engineering and business teams on best practices in performance tuning, debugging, and effectively leveraging Databricks Features.

Skills

Required

  • Apache Spark
  • Spark UI metrics
  • Mosaic AI Model Service
  • DAGs
  • event logs
  • Python
  • Java
  • Scala
  • Data Lakes
  • SQL-based databases
  • Cloud-based Data Warehousing/ETL tools
  • Snowflake
  • Redshift
  • Bigquery
  • Spark core internals
  • Delta/Iceberg
  • JVM optimization
  • memory management
  • Machine Learning
  • Deep Learning
  • Generative AI
  • AWS
  • Azure
  • GCP
  • CI/CD pipelines
  • monitoring
  • alerting systems
  • Technical Account Manager
  • Solutions Architect
  • communication
  • relationship-building
  • problem-solving
  • anticipate, identify, and mitigate risks
  • planning solutions for production challenges
  • business judgment
  • risk avoidance
  • cross-functional teams
  • senior leadership

What the JD emphasized

  • advanced Troubleshooting
  • Root Cause Analysis
  • performance and reliability issues
  • Spark/ML/AI runtime capabilities
  • production-scale Spark/ML/AI solutions
  • Deep knowledge of Spark core internals
  • Machine Learning, Deep Learning, and Generative AI
  • Advanced Proactive Problem Solving Skills

Other signals

  • customer-facing role
  • technical solutions
  • complex product issues
  • performance and reliability issues
  • Spark/ML/AI runtime capabilities