Senior Designated Support Engineer
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will troubleshoot complex Spark, SQL, Delta, streaming, and runtime issues. You will monitor customer environments, build and deploy proofs of concept, develop playbooks, train customer teams, and advocate for customers during engagements. You will work with technical stakeholders to resolve production-impacting problems and improve support processes.
Requirements
- 5 to 8 years of experience designing, building, and troubleshooting distributed computing applications
- 4+ years delivering production-scale Spark, ML, or AI solutions
- Python, Java, or Scala expertise
- Experience with data lakes, SQL databases, and cloud data warehousing or ETL tools
- Knowledge of Spark internals, Delta or Iceberg, JVM optimization, and memory management
- Knowledge of machine learning, deep learning, and generative AI
- Experience with AWS, Azure, or GCP
- Experience building CI/CD pipelines, monitoring, and alerting systems
- 3–5 years of customer-facing experience
- Experience collaborating with cross-functional teams and senior leadership
Responsibilities
- Troubleshoot and perform root-cause analysis for performance and reliability issues
- Define monitoring requirements to detect early performance issues
- Build, test, deploy, and monitor technical solutions
- Develop support playbooks and maintain a knowledge base
- Train customer teams on performance tuning and debugging
- Pilot best-practice processes and improve customer experience
- Advocate for customers in business reviews
- Collaborate onsite during customer engagements and technical presentations