Sr Designated Support Engineer

Databricks•San Francisco, CA

9h•$141,700 - $250,800

About The Position

The Sr Designated Support Engineer is a customer-facing technical subject matter expert who partners with Field and Engineering teams to provide high-touch specialized support and tailored technical solutions to Databricks’ largest and most strategic Digital Native Business (DNB) customers. The role uses expertise in Apache Spark and related data technologies to diagnose and resolve complex product issues and address critical customer challenges. It requires approximately 20% travel. The engineer performs advanced troubleshooting and root cause analysis across Spark, SQL, Delta, Streaming, and Databricks runtime features; develops rapid proofs of concept and validates solutions built by Databricks Engineering; and helps optimize customer environments in partnership with R&D and NOC teams. The role also develops playbooks and knowledge resources, trains customer teams, pilots process improvements, advocates for customers, and serves as a trusted technical advisor and primary point of contact. During customer engagements, the engineer collaborates onsite with Field Engineering, Sales, and Product teams to address production-impacting issues and deliver technical presentations.

Requirements

8–12 years of experience designing, building, and troubleshooting distributed computing applications.
At least 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 or ETL tools such as Snowflake, Redshift, or BigQuery.
Deep knowledge of Spark core internals, Delta/Iceberg, JVM optimization, and memory management.
Proficiency in AI ecosystems such as machine learning, deep learning, and generative AI.
Practical experience with AWS, Azure, or GCP.
Expertise building and managing CI/CD pipelines, monitoring, and alerting systems.
3–5 years of experience in customer-facing roles such as Technical Account Manager or Solutions Architect.
Strong communication, relationship-building, and problem-solving skills.
Ability to anticipate, identify, and mitigate risks and plan solutions for production challenges, using sound business judgment and coordinating team efforts and subject-matter expertise.
Proven ability to collaborate with cross-functional teams and senior leadership to address roadblocks, mitigate risks, and drive customer success.

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 such as Spark UI metrics, Mosaic AI Model Service, DAGs, and event logs.
Work with R&D and NOC teams to identify continuous-monitoring requirements and optimize DNB customer environments.
Build rapid proofs of concept and test, deploy, and monitor solutions developed by Databricks Engineering to address customer challenges and demonstrate Spark/ML/AI runtime capabilities aligned with business goals.
Develop playbooks and maintain a knowledge base of common issues and solutions for Spark, ML, and AI workflows.
Train customer engineering and business teams on performance tuning, debugging, and effective use of Databricks features.
Pilot new best-practice processes and programs, champion process improvements, and collaborate cross-functionally to improve 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 rapidly resolve production-impacting issues and build customer trust.
Create impactful documentation for self-service solutions and work with cross-functional teams and senior leadership to address roadblocks, mitigate risks, and drive customer success.