Data Engineer I - Payment Lifecycle Data

Requirements:

• Educational Background: Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Science, Econometrics, or a related quantitative/data discipline.
• Prior Experience: You have hands-on practical experience through a previous role or a technical internship (e.g., as a Data Engineer, Data Analyst, or Software Engineer looking to transition into Data Engineering).
• Core Technical Fundamentals: Strong proficiency in Python and SQL, with a passion for software craftspersonship and writing clean, maintainable code. Familiarity with Git-based workflows and CI/CD tooling, including version control, code reviews, automated testing, and deployment pipelines. Familiarity with orchestration engines (e.g., Airflow) or semantic layers/BI tools (e.g., dbt, Looker).
• Product Mindset: You are proactive, self-motivated, and eager to understand the real-world business impact of payments data. You get motivated by building data products that people will use.
• Curiosity: You have a genuine passion for data engineering and continuous learning, supported by a team ready to mentor your technical ramp-up.

What You'll Be Doing:

• End-to-End Data Product Ownership: Translate business questions into technical data solutions. Help scope, design, build, and validate data products alongside product managers and engineers.
• Build & Maintain ETL Pipelines: Help design, build, and operate high-quality production ETL pipelines and data architectures on our Big Data Platform using Python, Pyspark, and SQL.
• Stakeholder Collaboration: Engage directly with internal stakeholders to understand data needs, clarify requirements, and ensure high adoption of data products.
• Ensure High Data & Code Quality: Write clean, maintainable, and well-tested code. Implement testing, monitoring, and validation protocols using modern engineering tools.
• Learn & Modernise: Work with experienced Data Engineers to optimize data workflows, adopt modern developer tooling, and apply best practices in data governance and performance.

Nice to Haves (Bonus):

• Exposure to distributed data processing frameworks like PySpark or Spark.
• Prior experience with large production codebases or basic domain knowledge in global payments/fintech.

Perks and Benefits:

Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. No matter who you are or where you’re from, we welcome you to be your true self at Adyen.

At Adyen, we encourage applicants from all backgrounds to apply, even if they don't meet 100% of the qualifications. We value diversity and inclusion in our team.

This role is based out of our Amsterdam office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.