Data Engineer @ Adyen
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About Adyen
Adyen provides payments, data, and financial products in a single solution for clients like Meta, Uber, H&M, and Microsoft. At Adyen, everything we do is engineered for ambition. We create an environment with opportunities for our people to succeed, supported by a strong culture and career ownership.
Data Engineer Role at Adyen
At Adyen, data is a first-class citizen. As a Data Engineer, you will play a key role in maintaining data infrastructure and ensuring smooth data flows across systems. Based in our Amsterdam office, you will build high-quality data pipelines on our Big Data Platform.
What You’ll Do
- Collaborate with data scientists, analysts, engineers, product managers, and customers.
- Design, develop, deploy and operate production ELT pipelines and data architectures.
- Establish best practices in performance, code quality, data validation and governance.
- Implement testing, monitoring and validation protocols using tools like Pytest.
- Optimize performance, resolve bottlenecks and improve query efficiency using Spark optimizations.
Who You Are
- 3+ years of experience in a similar Data Engineering role.
- Solid background in software and data engineering practices.
- Proficient in Python, PySpark, Airflow, Hadoop, Spark, Kafka, SQL and Git.
- A clear communicator capable of explaining complex data concepts.
- A self-starter with an innovative and experimental mindset.
- A champion for data-centric culture and continuous improvement.
Diversity, Equity & Inclusion
Adyen values diverse perspectives and encourages applications from candidates of all backgrounds. We welcome you to be your true self.
What’s Next?
Expect a response within 5 business days, with an interview process lasting about 4 weeks. This role is office-first, based in Amsterdam.
Key skills/competency
- Data Pipelines
- ELT
- Big Data
- Python
- PySpark
- Airflow
- Hadoop
- Spark
- Kafka
- SQL
How to Get Hired at Adyen
🎯 Tips for Getting Hired
- Research Adyen's culture: Understand their mission, values, and recent news.
- Customize your resume: Highlight skills in Python, PySpark, and data pipelines.
- Demonstrate clarity: Showcase your experience in data architecture.
- Prepare for interviews: Focus on technical challenges and achievements.