Entry - Level Data Engineer at GM, focusing on building large scale data platforms in cloud environments. Collaborating with data engineers and scientists while migrating systems to cloud solutions.
About the role
- Apache Spark Specialist responsible for architecting and managing Spark environments on Nebul's AI cloud. Focus on performance, security, and solution innovation within a hybrid work environment.
Responsibilities
- 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
Requirements
- 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
- Competitive compensation
- Growth opportunities
- Equity participation in a critical market
Job title
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