Sr. Designated Support Engineer, Apache Spark

Databricks
Amsterdam, Netherlands
about 1 month ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Big Data Catalyst (Software) Directed Acyclic Graph (Directed Graphs) Data Architecture Information Engineering Extract Transform Load (ETL) Serialization Memory Management Issue Tracking Systems Python (Programming Language) DataOps
+4 more
Apache Spark Data Lakes Data Pipelines Databricks

Job description

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. This self-motivated professional will demonstrate high commitment to both customers and internal teams, with excellent communication, project management, and problem-solving skills. In this role, the Sr. Designated Support Engineer/Premier Support Engineer will build and maintain close relationships with strategic customers, manage and prioritize critical issues, and ensure a high-touch, proactive support experience. The Impact You Will Have

  • 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 (Delta Lake/Iceberg).
  • 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.
  • Successfully engage with Senior Leadership, Technical and Functional staff to remove roadblocks, address delays, and mitigate issues.
  • Effectively use sound business judgment, risk avoidance, and SME resources to coordinate team efforts to solve problems.
  • Carry out regular reviews of customer cases to identify trends and proactive optimization opportunities.
  • Champion and advocate for customers and chair roundtables to ensure close communication and relationship building with key stakeholders.
  • Drive customer self-sufficiency by ensuring customers understand how to engage with the Databricks Support organization and tools.

Requirements

  • 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. You are an excellent communicator (written and verbal skills), with demonstrable customer communication and coordination efforts, and the ability to take complex technical ideas and translate them to non-technical stakeholders
  • Preference for customer-facing experience as a Support Engineer, Technical Account Manager, DSE, or in related production support areas

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Good distractions

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