# Senior Designated Support Engineer

**Company:** [Databricks](https://hotfix.jobs/companies/databricks)
**Location:** Sydney, Australia
**Role:** Support Engineering
**Experience:** 5+ years
**Skills:** Spark, Python, Java, Scala, SQL, Data Lakes, Snowflake, Amazon Redshift, BigQuery, Delta Lake, Apache Iceberg, Jvm, AWS, CI/CD, Machine Learning
**Posted:** 2026-08-26

> Provides advanced, customer-facing technical support for strategic customers by diagnosing complex Spark and Databricks data and AI platform issues, developing solutions, and guiding performance optimization. Requires 5+ years in distributed computing and strong production-scale Spark expertise.

## 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 involving Spark, SQL, Delta, streaming, and Databricks runtime features.
- Use Spark UI metrics, Mosaic AI Model Service, DAGs, and event logs to diagnose complex product issues.
- Define continuous-monitoring requirements and collaborate with R&D and NOC teams to optimize customer environments.
- Build rapid proofs of concept; test, deploy, and monitor Databricks Engineering solutions addressing customer challenges.
- Develop playbooks and maintain knowledge bases covering 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 enhance customer experience.
- Advocate for customers in business reviews and serve as a trusted advisor and primary technical point of contact.
- Collaborate onsite with Field Engineering, Sales, and Product teams during customer engagements and technical presentations.

## Requirements
- 5–8 years 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-based databases, and cloud data warehousing or ETL tools.
- Deep knowledge of Spark internals, Delta or Iceberg, JVM optimization, and memory management.
- Proficiency in machine learning, deep learning, and generative AI ecosystems.
- Experience with AWS, Azure, or Google Cloud.
- Experience building and managing CI/CD pipelines, monitoring, and alerting systems.
- 3–5 years in customer-facing roles such as Technical Account Manager or Solutions Architect.
- Strong communication, relationship-building, problem-solving, documentation, and cross-functional collaboration skills.
- Ability to anticipate and mitigate risks, coordinate technical resources, and address production challenges.

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