Databricks

Overview

Databricks is seeking an experienced Sr. Designated Support Engineer/Premier Support Engineer with a strong technical foundation in Apache Spark and a passion for customer engagement to build and maintain close relationships with strategic customers, manage and prioritize critical issues, and ensure a high-touch, proactive support experience.

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse,

Requirements & Eligibility

• Minimum 3 years of dedicated experience in Data Engineering, building, deploying, and maintaining large-scale data pipelines.
• Minimum 3 years’ experience designing, developing, testing, and sustaining Python/Java/Scala-based applications required.
• Deep, architectural knowledge of Apache Spark internals (including Drivers, Executors, Core Memory Management, DAGs, Catalyst Optimizer, and Tungsten execution engine).
• Proven track record of troubleshooting complex Spark and big data issues, such as data skew, out-of-memory (OOM) errors, serialization issues, and slow-running broadcast joins.
• Highly effective with project managing multiple tasks and work streams, driving them to conclusion.
• Demonstrated analytical and problem-solving skills, particularly those that apply to a Distributed Big Data Computing environment.
• Excellent executive presence with demonstrable customer communication and coordination efforts.

Key Responsibilities

• Manage large strategic accounts to provide a high-touch support experience.
• Deep-dive into complex Apache Spark and Data Engineering issues, analyzing Spark UI, thread dumps, and driver/executor logs to resolve critical performance bottlenecks.
• Advise strategic customers on Data Engineering best practices, including optimizing ETL/ELT pipelines, data modeling, and leveraging the Databricks Lakehouse architecture.
• Project manage all open support cases to expedite support ticket closure.
• Facilitate customer correspondence with Engineering, Product Team, SMEs, and Accounts Teams to advance tickets toward resolution.
• Directly engage on business-impacting situations and ensure recovery of functionality for the customer.
• Carry out regular reviews of customer cases to identify trends and proactive optimization opportunities.
• Drive customer self-sufficiency by ensuring customers understand how to engage with the Databricks Support organization and tools.