Sr. Designated Support Engineer, Apache Spark™
Databricks · Amsterdam, Netherlands · Support · listed August 19, 2025
The shape of it
Seniority
Senior
Experience asked
3+ years
Where
Not stated
Requirements listed
8
Length
984 words
In the posting’s own words
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
What it asks for · 8
- 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
What the job covers
- 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.
Tools and skills named
Data
- Spark14×
- Databricks5×
- ETL4×
- Data modeling2×
- Data pipelines2×
- Data warehouse2×
Languages
- Java2×
- Python2×
- Scala2×
Ways of working
- Testing2×
Operations & finance
- Project management
Words the posting leans on
- customer19×
- data16×
- support15×
- issues9×
- spark9×
- experience8×
- complex6×
- data engineering6×
- engage6×
- technical6×
- accounts5×
- apache spark5×
- communication5×
- ensure5×
- excellent5×
- manage5×
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