Data Engineering

Xccelerated; Amsterdam; On-site; EUR 75,000 - 110,000; Full time

Job summary

Xccelerated in Amsterdam is seeking a Data Engineer to design, build and maintain scalable data infrastructure and data-intensive systems. You will contribute to modern data platforms and collaborate across data, product and business teams.

You start with a two-week alignment and then work embedded with partner engineering teams four days a week, returning to Amsterdam for deep-dives. The role focuses on production-grade data pipelines, cloud platforms and continuous improvement to deliver real

Qualifications

• 3–5 years of experience as a Data Engineer or Software Engineer.
• Hands-on experience with Spark, Kafka, Airflow and Kubernetes.
• Experience with at least one major cloud platform (Azure, GCP or AWS).
• Strong communication and collaboration across stakeholders.

Responsibilities

• Design, build and maintain scalable data infrastructure.
• Ensure production readiness and clean architecture.
• Make data accessible across teams.
• Collaborate with data scientists and engineers.

Skills

Communication

Collaboration

Problem-solving

Education

Bachelor's or Master's in Computer Science / Software Engineering

Tools

Spark

Kafka

Airflow

Kubernetes

Job description

Data Engineering at Xccelerated

Engineer modern data platforms that power real business impact.

Data Engineers are the engineers behind modern data platforms. You architect and build scalable systems that move, transform and store data at scale. From cloud-native warehouses and lakehouses to distributed data meshes, you lay the foundation for analytics and AI. Together with data scientists, you operationalize, monitor and scale machine learning solutions and data products in production.

Technical alignment phase

Every Data Engineer starts with a focused two-week engineering alignment phase. This intensive period sharpens production-ready Python, containerization, large-scale data processing with Apache Spark and Kafka, and core cloud engineering principles. Rather than classroom-style learning, you work hands‑on through practical engineering challenges and realistic scenarios. Our Data Engineering Lead tailors the approach to your background to ensure a strong and consistent technical foundation before entering complex production environments.

The first 12 months

After the alignment phase, you join one of our partner organizations four days a week, embedded in a real engineering team. On the fifth day, you return to Xccelerated in Amsterdam for advanced deep‑dives, architecture reviews and technical sparring. These sessions focus directly on the challenges you encounter in your project, while expanding your expertise across modern data engineering domains. At the end of the year, you transition into a permanent role at the partner organization.

Technical focus areas

• Production-grade Data Engineering with Python & Scala
• Deploying and operationalizing Machine Learning models
• Distributed data processing with Kafka and Spark
• Workflow orchestration with Apache Airflow
• Containerization and runtime environments with Docker
• Data storage architectures, lakes and lakehouses
• Distributed Systems design principles
• Cloud-native data platform engineering
• Engineering leadership and communication
• Professional growth and impact development

Why work at Xccelerated?

Technical acceleration

Work with senior Tech Leads on architecture decisions, scalable data and cloud-native patterns, CI/CD, advanced modeling and platform design. We don’t repeat basics. We refine how you build.

Real production impact

You work in complex environments, contributing to modern data and cloud platforms, migrations or greenfield builds. No simulations. No sandbox projects. Just real systems at scale.

Like-minded professionals

Work in an international environment with like-minded professionals who are on the same page: learning, making impact, sharing knowledge and having fun.

Engineering Leadership & Communication

Alongside deep technical development, we focus on the skills required to operate effectively in complex engineering environments. This includes strengthening your ability to communicate technical decisions clearly and create alignment across data, product and business teams.

These sessions are centered around personal leadership, professional growth and influencing without authority. You gain insight into your communication style, decision‑making patterns and development goals. We work on stakeholder management, structured feedback, presenting technical concepts and navigating conflict in high‑impact environments.

This development track consists of several focused sessions spread throughout the year, each designed as an interactive workshop where you actively practice and apply what you learn in real project scenarios.

The skills I learned at Xccelerated are incredibly valuable—I use them everyday at work. After the bootcamp, I had the feeling that I wanted to rewrite all my previous projects.

Nikki Doorhof - data scientist, Xccelerated/Nationale Nederlanden

Xccelerated decreases the gap between software engineering and data science. Thanks to this, I’m solving real data engineering challenges.

Selin Gungor - data engineer, Xccelerated/ING

I’m impressed by the guidance I get from the many experts I’m surrounded with at Xccelerated. It helps me become an expert myself as well at Heineken.

Aldy Syahdeini - cloud developer, Xccelerated/Heineken

Ready to deepen your impact as a Data Engineer?

As a Data Engineer at Xccelerated, you work alongside experienced engineers on complex, high-impact projects for leading organizations. You contribute directly to modern data platforms and help industrialize machine learning at scale.

You design, build and maintain scalable data infrastructure and data-intensive systems. You care about clean architecture, production readiness and making reliable data accessible across teams.

• A technical bachelor’s or master’s degree (e.g. Computer Science, Informatics, Artificial Intelligence, Software Engineering)
• 3–5 years of experience as a Data Engineer or Software Engineer
• Hands‑on experience with technologies such as Spark, Kafka, Airflow and Kubernetes
• Experience with at least one major cloud platform (Azure, GCP or AWS)
• Strong communication skills and the ability to collaborate across technical and non‑technical stakeholders