Staff Designated Support Engineer
Databricks
Bengaluru, IndiaonsitePosted 1 month ago
Skill Required
EngineeringQuery OptimizationMachine LearningData WarehousingDeep LearningGenerative AICD pipelinesDatabricksObservabilitySnowflakedesigningdebuggingBigQueryRedshiftbuildingPythonScalaSparkAzureCI/CDUnityCloudJavaETLSQL
Key highlights
- Level Required: 8–12 years in Spark/ML/AI solutions
- Key benefit: Comprehensive benefits package (specifics unspecified)
- Notable requirement: Proficiency in Apache Spark core internals and Delta/Iceberg
- Customer-facing experience: 3–5 years in roles like Technical Account Manager
Role overview
The role of Staff Designated Engineer at Databricks involves providing specialized technical support and tailored solutions to high-priority customers in the Digital Native Business (DNB) segment. The engineer will leverage deep expertise in Apache Spark and data technologies to troubleshoot complex issues, deliver proof-of-concepts, and collaborate with cross-functional teams to enhance customer success. Key responsibilities include root cause analysis, process optimization, training, and acting as a trusted advisor to ensure customer satisfaction.
Responsibilities
- Partner with Field and Engineering teams to deliver specialized technical support for Databricks' largest customers
- Perform advanced troubleshooting and root cause analysis for performance and reliability issues in Spark, SQL, Delta, Streaming, and Databricks runtime features
- Build and deploy rapid proofs-of-concept (POCs) to address customer challenges using Spark/ML/AI capabilities
- Develop playbooks and maintain a knowledge base for Spark, ML, and AI workflows
- Train customer engineering and business teams on performance tuning, debugging, and Databricks features
- Pilot new processes and champion improvements to enhance customer experience
- Advocate for customers in business review meetings and serve as the primary technical point of contact
- Collaborate onsite with Field Engineering, Sales, and Product teams during technical presentations to resolve production-impacting issues
Requirements
- 8–12 years of experience designing, building, and troubleshooting distributed computing applications, with 4+ years delivering production-scale Spark/ML/AI solutions
- Hands-on expertise with Data Lakes, SQL-based databases, and cloud data warehousing/ETL tools (e.g., Snowflake, Redshift, BigQuery)
- Deep knowledge of Spark core internals, Delta/Iceberg, JVM optimization, and memory management, with additional proficiency in AI ecosystems (ML, Deep Learning, Generative AI)
- Practical experience with AWS, Azure, or GCP, along with expertise in CI/CD pipelines, monitoring, and alerting systems
- 3–5 years in customer-facing roles (e.g., Technical Account Manager or Solutions Architect) with strong communication and problem-solving skills
- Proven ability to anticipate risks, mitigate production challenges, and coordinate team efforts using business judgment and SME resources
Additional details
- Company commitment to diversity and inclusion with inclusive hiring practices
- Compliance requirement for export-controlled technology access (U.S. government license discretion)
- Reference to Databricks' global presence (30+ offices) and product suite (Genie, Lakebase, Agent Bricks, etc.)
- Mention of specific collaboration requirements (R&D, NOC, Field teams)