Big Data Engineer, Spark

Nebul

full-time

Posted on: 1/13/2026

Location Type: Hybrid

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About the role

Architect, deploy, and operate scalable Apache Spark environments on Nebul’s sovereign AI cloud
Design and optimize Spark workloads for GPU-accelerated and distributed performance
Define and implement best practices for security, monitoring, governance, and data protection
Partner closely with product, engineering, and customer teams to shape our managed Spark offering
Evaluate and integrate complementary technologies (e.g., Delta Lake, Lakehouse components, tooling)
Support early customer pilots and translate feedback into roadmap improvements
Develop automation and CI/CD deployment models to ensure reliability, repeatability, and efficiency
Document architectures, operational procedures, and performance benchmarks

4–7 years of experience working with Apache Spark in production environments
Strong deep-dive knowledge of Spark internals: performance tuning, partition strategies, caching, and shuffle management
Hands-on deployment experience in Kubernetes, cloud infrastructure, or on-prem clusters
Solid understanding of distributed data platforms (e.g., Databricks, EMR, Hadoop, Lakehouse architectures)
Strong scripting and automation skills (Python / Scala preferred)
Ability to translate client needs into technical architectures and operational models
Familiarity with cloud-security principles and infrastructure-as-code practices
Valid EU work permit (no sponsorship currently available)
Fluent in English (Dutch not required)

Benefits

Tip: use these terms in your resume and cover letter to boost ATS matches.

Apache Sparkperformance tuningpartition strategiescachingshuffle managementKubernetesPythonScalaautomationCI/CD

collaborationcommunicationproblem-solvingclient needs translationdocumentation

valid EU work permit