Senior Designated Support Engineer

Databricks
Sydney
Workplace: OnsiteFull timeFunction: Design (Product/UX/UI/Visual)Experience: 5-8 yearsSkills: ["Communication","Relationship-building","Problem-solving","Collaboration","Risk mitigation"]

Deliver high-touch, customer-facing technical support for Databricks’ most strategic Digital Native Business customers. Troubleshoot and perform root-cause analysis for complex performance and reliability issues across Spark, SQL, Delta, streaming, and runtime features. Build rapid POCs, create playbooks and knowledge bases, and train customer teams on performance tuning. Partner with Field, Engineering, Sales, and Product—often onsite—to unblock production-critical challenges.

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FursaFursa
Databricks
Databricks
3 days ago

Senior Designated Support Engineer

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Last checked: 3 hours agoStatus: Live

Job Summary

Deliver high-touch, customer-facing technical support for Databricks’ most strategic Digital Native Business customers. Troubleshoot and perform root-cause analysis for complex performance and reliability issues across Spark, SQL, Delta, streaming, and runtime features. Build rapid POCs, create playbooks and knowledge bases, and train customer teams on performance tuning. Partner with Field, Engineering, Sales, and Product—often onsite—to unblock production-critical challenges.
Location: Sydney
Workplace: Onsite
Employment Type: Full time
Job Function: Design (Product/UX/UI/Visual)
Seniority: Mid level

Key Responsibilities

  • •Troubleshoot and perform root-cause analysis for Spark, SQL, Delta, streaming, and Databricks runtime performance and reliability issues using metrics, AI model service tools, DAGs, and event logs.
  • •Set up continuous monitoring to detect early performance issues, partnering with R&D and NOC teams to optimize Digital Native Business customer environments.
  • •Build rapid POCs and test/deploy/monitor solutions created by Databricks Engineering to address customer challenges and demonstrate Spark/ML/AI capabilities.
  • •Create playbooks and maintain a knowledge base for common Spark, ML, and AI workflows; train customer engineering and business teams on best practices for tuning and debugging.
  • •Serve as a trusted technical point of contact by coordinating risk mitigation and collaborating onsite with Field Engineering, Sales, and Product during customer engagements and presentations.

Key Requirements

  • •5 to 8 years designing, building, and troubleshooting distributed computing applications, with 4+ years delivering production-scale Spark/ML/AI solutions using Python, Java, or Scala.
  • •Hands-on specialization in Data Lakes, SQL-based databases, and cloud data warehousing/ETL tools such as Snowflake, Redshift, or BigQuery.
  • •Deep knowledge of Spark core internals, Delta/Iceberg, JVM optimization, and memory management, plus proficiency with Machine Learning, Deep Learning, and Generative AI ecosystems.
  • •Practical cloud and CI/CD experience with AWS, Azure, or GCP, including building/managing CI/CD pipelines, monitoring, and alerting systems.
  • •Customer-facing experience (3–5 years) in roles such as Technical Account Manager or Solutions Architect, demonstrating strong communication, relationship-building, and problem-solving.
Experience:5-8 yearsBig dataData engineeringCloud
Skills:CommunicationRelationship-buildingProblem-solvingCollaborationRisk mitigation
Languages:English
Tech Stack:Apache SparkSpark UISQLDeltaIcebergStreamingDatabricks runtimeMosaic AI Model ServiceDAGsEvent logsPythonJavaScalaData LakesSnowflakeRedshiftBigQueryMachine LearningDeep LearningGenerative AI

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