Staff Designated Support Engineer

Databricks
San Francisco
Workplace: OnsiteFull timeFunction: Design (Product/UX/UI/Visual)Skills: ["Communication","Leadership","Problem-solving","Customer-facing","Training"]

Senior, customer-facing technical solutions engineer focused on high-touch support for Databricks’ largest customers. You will apply Apache Spark and data technologies to triage issues, build rapid POCs, develop playbooks, and train teams while collaborating with Field, Engineering, and Product to improve customer success and technical outcomes.

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FursaFursa
Databricks
Databricks
1 year ago

Staff Designated Support Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Senior, customer-facing technical solutions engineer focused on high-touch support for Databricks’ largest customers. You will apply Apache Spark and data technologies to triage issues, build rapid POCs, develop playbooks, and train teams while collaborating with Field, Engineering, and Product to improve customer success and technical outcomes.
Location: San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Design (Product/UX/UI/Visual)

Key Responsibilities

  • •Collaborate with Field Engineering, Sales, and Product teams to provide rapid, production-impacting solutions during customer engagements.
  • •Perform advanced troubleshooting and root cause analysis to resolve performance and reliability issues in Spark, SQL, Delta, Streaming, and Databricks runtime features.
  • •Build rapid proofs-of-concept, test/deploy/monitor solutions, and showcase advanced Spark/ML/AI runtime capabilities tied to customer goals.
  • •Develop playbooks and maintain a knowledge base for Spark, ML, and AI workflows to enable self-service support.
  • •Train customer engineering and business teams on performance tuning, debugging, and best practices for leveraging Databricks features.

Key Requirements

  • •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.
  • •Hands-on expertise with Data Lakes, SQL-based databases, and Cloud-based Data Warehousing/ETL tools like Snowflake, Redshift, BigQuery, etc.
  • •Deep knowledge of Spark core internals, Delta/Iceberg, JVM optimization, and memory management, plus proficiency in ML/AI ecosystems.
  • •Practical experience with AWS, Azure, or GCP, and building/managing CI/CD pipelines, monitoring, and alerting systems.
  • •3–5 years in customer-facing roles such as Technical Account Manager or Solutions Architect, with strong communication and problem-solving skills.
Experience:Big dataSparkData engineering
Skills:CommunicationLeadershipProblem-solvingCustomer-facingTraining
Languages:English
Tech Stack:Apache SparkPythonJavaScalaSnowflakeRedshiftBigQuerySpark UIDeltaIcebergJVMAWSAzureGCPCI/CDMonitoringAlertingMLAIDatabricks

Company Brief

Databricks
Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.
Industry: Data Infrastructure
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2013
WebsiteLinkedIn