# Staff Designated Support Engineer

**Company:** [Databricks](https://hotfix.jobs/companies/databricks)
**Location:** Sydney, Australia
**Role:** Support Engineering
**Experience:** 8+ years
**Skills:** Spark, Python, Java, Scala, SQL, Delta Lake, Apache Iceberg, Jvm, Machine Learning, Generative AI, AWS, Azure, GCP, CI/CD, Snowflake
**Posted:** 2026-08-22

> Provides advanced, customer-facing troubleshooting and technical solutions for strategic Databricks customers, specializing in Spark, data engineering, ML, and AI workloads. Requires 8+ years in distributed computing, production-scale Spark solutions, cloud and CI/CD expertise, and fluent Japanese with business-level English.

## Job Description

## Responsibilities
- Provide high-touch, specialized technical support and tailored solutions for strategic Digital Native Business customers.
- Troubleshoot and perform root-cause analysis for performance and reliability issues across Apache Spark, SQL, Delta, streaming, and Databricks Runtime features.
- Use Spark UI metrics, DAGs, event logs, and related tools to diagnose complex product issues.
- Define continuous-monitoring requirements with R&D and NOC teams to optimize customer environments.
- Build rapid proofs of concept and test, deploy, and monitor Databricks Engineering solutions.
- Develop playbooks and maintain knowledge bases for Spark, ML, and AI workflows.
- Train customer engineering and business teams on performance tuning, debugging, and Databricks best practices.
- Pilot process improvements and collaborate cross-functionally to improve customer experience.
- Advocate for customers in business reviews and serve as a trusted advisor and primary technical contact.
- Collaborate with Field Engineering, Sales, and Product teams during customer engagements and technical presentations.

## Requirements
- 8–12 years of experience designing, building, and troubleshooting distributed computing applications.
- 4+ years delivering production-scale Spark, ML, or AI solutions using Python, Java, or Scala.
- Hands-on expertise with data lakes, SQL databases, and cloud data warehousing or ETL tools.
- Deep knowledge of Spark internals, Delta or Iceberg, JVM optimization, and memory management.
- Proficiency with machine learning, deep learning, and generative AI ecosystems.
- Experience with AWS, Azure, or Google Cloud and CI/CD pipelines, monitoring, and alerting systems.
- 3–5 years of customer-facing experience in roles such as Technical Account Manager or Solutions Architect.
- Strong problem-solving, risk management, communication, relationship-building, documentation, collaboration, and leadership skills.
- Fluent Japanese and business-level English.

## Preferred Technologies
- Snowflake
- Amazon Redshift
- BigQuery

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