Senior Designated Support Engineer (Spark/AI)

Location: Sydney, Australia

Company

Databricks provides a unified Data + AI Platform for building and scaling data, analytics, and AI applications.

What you will do

• Provide high-touch technical support and tailored solutions for strategic Digital Native Business customers.
• troubleshoot and perform root cause analysis for performance and reliability issues across Spark, SQL, Delta, streaming, and Databricks Runtime features.
• Develop monitoring requirements, rapid proofs of concept, and solutions for customer production challenges.
• Test, deploy, and monitor solutions built with Databricks Engineering, including advanced Spark, ML, and AI runtime capabilities.
• Create technical playbooks and knowledge-base content, and train customer teams on debugging and performance tuning.
• Partner with Field Engineering, Sales, Product, R&D, and NOC teams as a trusted technical advisor during customer engagements.

Requirements

• 5–8 years of experience designing, building, and troubleshooting distributed computing applications.
• 4+ years delivering production-scale Spark, ML, or AI solutions with Python, Java, or Scala.
• Hands-on experience with data lakes, SQL databases, cloud data warehousing, and ETL tools such as Snowflake, Redshift, or BigQuery.
• Deep knowledge of Spark internals, Delta or Iceberg, JVM optimization, and memory management.
• Experience with AWS, Azure, or GCP, plus CI/CD pipelines, monitoring, and alerting systems.
• 3–5 years of customer-facing experience in roles such as Technical Account Manager or Solutions Architect, with strong communication and problem-solving skills.

Culture & Benefits

• Collaboration with cross-functional teams and senior leadership to drive customer success.
• Opportunities to improve support processes and create self-service technical documentation.
• Comprehensive benefits and perks, with details varying by region.
• Commitment to an inclusive workplace and equal employment opportunity.