P-1011 Job Location: San Francisco Bay Area, CA As a Sr. Staff Technical Solutions 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 Business (DNB) segment. In this customer-facing role, you will leverage your technical expertise in Apache Spark™ and other data technologies to triage and resolve complex product issues and unblock our customers’ most critical technical challenges
The Impact You Will Have 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
What We Look For Technical Expertise in Big Data and Spark: 8–12 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 Advanced Tech Skills : Deep knowledge of Spark core internals, Delta/Iceberg, JVM optimization, and memory management, with additional proficiency in AI ecosystems like Machine Learning, Deep Learning, and Generative AI