Staff Designated Support Engineer

Databricks
Sydney
Workplace: OnsiteFull timeFunction: Design (Product/UX/UI/Visual)Experience: 10+ yearsSkills: ["Communication","Relationship-building","Problem-solving","Collaboration","Risk mitigation"]

Deliver high-touch technical support to Databricks’ largest strategic customers, partnering with Field and Engineering teams to triage and resolve complex issues across Spark, SQL, Delta, streaming, and Databricks runtime features. Perform advanced troubleshooting and root-cause analysis, develop rapid POCs, and build playbooks and knowledge bases. Train customers on performance tuning and debugging best practices, and collaborate onsite during engagements and technical presentations.

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FursaFursa
Databricks
Databricks
3 days ago

Staff Designated Support Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 3 hours agoStatus: Live

Job Summary

Deliver high-touch technical support to Databricks’ largest strategic customers, partnering with Field and Engineering teams to triage and resolve complex issues across Spark, SQL, Delta, streaming, and Databricks runtime features. Perform advanced troubleshooting and root-cause analysis, develop rapid POCs, and build playbooks and knowledge bases. Train customers on performance tuning and debugging best practices, and collaborate onsite during engagements and technical presentations.
Location: Sydney
Workplace: Onsite
Employment Type: Full time
Job Function: Design (Product/UX/UI/Visual)
Seniority: Mid level

Key Responsibilities

  • •Perform advanced troubleshooting and root cause analysis to resolve performance and reliability issues in Spark, SQL, Delta, streaming, and Databricks runtime features.
  • •Identify requirements for continuous monitoring and work with R&D and NOC teams to optimise DNB customer environments.
  • •Build rapid POCs and test/deploy/monitor solutions delivered by Databricks Engineering to address customer challenges.
  • •Develop comprehensive playbooks and maintain a knowledge base for common issues and solutions in Spark, ML, and AI workflows.
  • •Train and advise customer engineering and business teams on best practices for performance tuning, debugging, and leveraging Databricks features; collaborate onsite during engagements.

Key Requirements

  • •10+ years designing, building, and troubleshooting distributed computing applications, including 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 such as Snowflake, Redshift, or BigQuery.
  • •Deep knowledge of Spark core internals, Delta/Iceberg, JVM optimisation, and memory management, plus proficiency in machine learning, deep learning, and generative AI ecosystems.
  • •Practical experience with AWS, Azure, or GCP, including building and managing CI/CD pipelines, monitoring, and alerting systems.
  • •3–5 years in customer-facing roles (e.g., Technical Account Manager or Solutions Architect) demonstrating strong communication, relationship-building, and problem-solving.
Experience:10+ yearsBig dataApache SparkData engineeringAI/MLCloud data warehousingCustomer-facing roles
Skills:CommunicationRelationship-buildingProblem-solvingCollaborationRisk mitigation
Languages:English
Tech Stack:Apache SparkSpark UIMosaic AI Model ServiceDeltaIcebergSQLPythonJavaScalaJVM optimizationMemory managementMachine LearningDeep LearningGenerative AIAWSAzureGCPCI/CDMonitoringAlerting

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