Build and evolve the core platform for data and AI at scale. Work on high-scale Kubernetes, complex distributed systems, and real reliability challenges. Drive system reliability, availability, and performance.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
SRE - Data Platform Engineer - Kubernetes - top 0,5% biggest data set globally
Amsterdam (Hybrid) - Visa sponsorship and relocation included
Building the backbone of data & AI at scale. This is not a “keep the lights on” role.
If you are interested in:
- Working on systems where failure is not an option
- A team that values engineering quality over shortcuts
- Real ownership — you build it, you run it, you improve it
- Growth paths in deep technical expertise or leadership
- A setup where your work has visible, measurable impact
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You’ll be building and evolving the core platform that everything depends on—from data pipelines to machine learning and real-time AI services. Think high-scale Kubernetes, complex distributed systems, and real reliability challenges where your decisions actually matter.
If you care about uptime, performance, and engineering systems that don’t break under pressure, this is your kind of environment.
Why this role stands out for SREs / Platform Engineers
- Reliability is the product — not an afterthought
- Work on real-world scale problems (not toy infra)
- Balance batch, streaming, and real-time workloads in one platform
- Tackle non-trivial Kubernetes challenges (scheduling, multi-tenancy, resource isolation)
- Own systems that directly impact data, ML, and AI products
- High autonomy, high responsibility, low bureaucracy
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You’re not just supporting engineers — you’re enabling an entire ecosystem.
What you’ll actually do
- Build and scale Kubernetes-based platform infrastructure, keeping systems highly available under unpredictable load
- Drive system reliability, availability, and performance. Preventing resource contention between critical and heavy workloads
- Building secure, multi-tenant platforms without performance trade-offs
- Automate everything that shouldn’t require human intervention
- Design solutions for high-throughput, data-heavy workloads. Running GPU-powered and compute-intensive workloads efficiently.
- Optimize scalability. Scaling storage and networking for massive data volumes. Designing smart autoscaling and cost-efficient infrastructure.
- Support and unblock internal teams using the platform
- Continuously improve observability, alerting, and incident response
- Be part of an on-call rotation where reliability truly matters
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You:
- Have solid experience in SRE, Platform, or Infrastructure Engineering for data platforms or big data tooling.
- Are comfortable with Kubernetes in production environments
- Understand distributed systems and failure modes
- Care deeply about reliability, observability, and automation
- Enjoy solving complex problems rather than following playbooks
- Exposure to high-performance workloads or GPU environments
Salary and benefits
The base salary is between 90K and 150K euro, depending on what you bring to the table in terms of skills, personality and experience.
Some of the secondary benefits: a permanent contract, 20% guaranteed bonus in stock, 10K+ personal allowance (can be used as extra salary), healthcare allowance (~2K a year), holiday allowance (8%), holidays, laptop, travel allowance, relocation package for Internationals, training & conferences, 30% ruling, VISA sponsorship, luxury lunch, snacks/drinks, work from home setup, etc.
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