Description
As a Staff Designated Support Engineer at Databricks, you will partner closely with Field and Engineering teams to deliver high-touch specialised support and tailored technical solutions for Databricks' largest and most strategic customers in the Digital Native Business (DNB) segment.
The Impact You Will Have
You will perform advanced troubleshooting and root cause analysis to resolve performance and reliability issues in Spark, SQL, Delta, Streaming, and Databricks runtime features using tools like Spark UI metrics, Mosaic AI Model Service, DAGs, and event logs.
Key responsibilities include:
- Discovering requirements for continuous monitoring to detect early performance issues working with R&D and NOC teams to optimise DNB customer environments.
- Building rapid POCs, testing/deploying/monitoring solutions built by Databricks Engineering to address customer challenges and showcase advanced Spark/ML/AI runtime capabilities aligned with their business goals.
- Developing comprehensive playbooks and maintaining a knowledge base of common issues and solutions for Spark, ML, and AI workflows.
- Training customer engineering and business teams on best practices in performance tuning, debugging, and effectively leveraging Databricks Features.
- Piloting new best practices processes/programs, championing process improvements, and collaborating with cross-functional teams to enhance the customer experience.
- Advocating for customers in business review meetings and maintaining close relationships as a trusted advisor and primary technical point of contact.
- Collaborating onsite with Field Engineering, Sales, and Product teams during customer engagements and technical presentations to provide rapid solutions to production-impacting issues.
What We Look For
We are looking for someone with:
- Technical expertise in Big Data and Spark: 8–12 years of experience designing, building, and troubleshooting distributed computing applications, with 4+ years delivering production-scale Spark/ML/AI solutions using Python, Java, or Scala.
- Data Engineering Specialisation: Hands-on expertise with Data Lakes, SQL-based databases, and Cloud-based Data Warehousing/ETL tools like Snowflake, Redshift, Bigquery, etc.
- Advanced tech skills: Deep knowledge of Spark core internals, Delta/Iceberg, JVM optimisation, and memory management, with additional proficiency in AI ecosystems like Machine Learning, Deep Learning, and Generative AI.
- Cloud and CI/CD Skills: Practical experience with AWS, Azure, or GCP, coupled with expertise in building and managing CI/CD pipelines, monitoring, and alerting systems.
- Customer-facing experience: 3–5 years in customer-facing roles such as Technical Account Manager or Solutions Architect, demonstrating strong communication, relationship-building, and problem-solving skills.
- Advanced proactive problem-solving skills: Proven ability to anticipate, identify, and mitigate risks while planning solutions for production challenges.
- Collaboration and leadership: Proven ability to work with cross-functional teams and senior leadership to address roadblocks, mitigate risks, and drive customer success.
Pay Range Transparency
The pay range for this role is $141,700-$250,800 USD.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.