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Sr Designated Support Engineer

Databricks· Engineering
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San Francisco Bay Area, CA$141.7k - $250.8kFull-timePosted 5d ago

About the role

Senior staff technical solutions engineer focused on high-touch, specialized support for Databricks' largest customers in the Digital Native Business segment. Requires deep expertise in Apache Spark and related data tech, with customer-facing responsibilities, troubleshooting, and collaboration across Field, Engineering, and Product teams.

Responsibilities

  • 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.
  • 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.

Qualifications

  • 8–12 years of experience designing, building, and troubleshooting distributed computing applications.
  • 4+ years delivering production-scale Spark/ML/AI solutions using Python, Java, or Scala.
  • Hands-on expertise with Data Lakes, SQL-based databases, and Cloud-based Data Warehousing/ETL tools like Snowflake, Redshift, BigQuery.
  • Deep knowledge of Spark core internals, Delta/Iceberg, JVM optimization, memory management; proficiency in AI ecosystems (ML, DL, Generative AI).
  • Practical experience with AWS, Azure, or GCP; expertise in building and managing CI/CD pipelines, monitoring, and alerting systems.
  • 3–5 years in customer-facing roles (e.g., Technical Account Manager, Solutions Architect).
  • Proven ability to anticipate, identify, and mitigate risks; strong business judgment and collaboration across teams.
  • Ability to work with cross-functional teams and senior leadership; produce impactful self-service documentation.

Skills

Required:Delta Lake / Iceberg

Benefits

  • Comprehensive benefits package as described by Databricks.
  • Region-specific details available via benefits page.
Last updated Oct 22, 2026. Interested? Apply on the company site.

About Databricks

Leading Data and AI Platform for Enterprises

Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data Intelligence Platform.

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