Senior Designated Support EngineerActive

Databricks
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The opportunity

As a Senior Designated Engineer and tech subject matter expert, you will partner closely with our Field and Engineering teams to deliver high-touch specialized support and tailored technical solutions for Databricks' largest and most strategic customers in the Digital Native…

What you'll do

  • 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.

  • Discover requirements for continuous monitoring to detect early performance: issues working with R&D and NOC teams to optimize the DNB customer environments.

  • 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.

  • Develop comprehensive playbooks and maintain a knowledge base of common: issues and solutions for Spark, ML, and AI workflows.

  • Train customer engineering and business teams on best practices in: performance tuning, debugging, and effectively leveraging Databricks Features.

  • Pilot new best practices processes/ programs, champion process improvements,: and collaborate with cross-functional teams to enhance the customer experience.

What they're looking for

  • Advocate for customers in business review meetings and maintain close: relationships as a trusted advisor and primary technical point of contact.
  • Collaborate onsite with Field Engineering, Sales, and Product teams during: customer engagements and technical presentations to provide rapid solutions to production-impacting issues, demonstrating deep technical expertise and building strong customer trust.
  • Technical Expertise in Big Data and Spark: 5 – 8 years of experience designing, building, and troubleshooting distributed computing applications, with 4+ years delivering production-scale Spark/ML/AI solutions using Python, Java, or Scala.
  • Data Engineering Specialization: Hands-on expertise with Data Lakes, SQL-based databases, and Cloud-based Data Warehousing/ETL tools like Snowflake, Redshift, Bigquery, etc