Data Engineer I - Payment Lifecycle Data

<p><strong>This is Adyen</strong></p> <p><span style="font-weight: 400;">Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&amp;M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition.&nbsp;</span></p> <p><span style="font-weight: 400;">For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.</span></p> <p><strong>Data Engineer I - Payment Lifecycle Data</strong></p> <p>At Adyen, we treat data and data artifacts as first-class citizens. They form our backbone and directly drive the business, product, and operational insights we generate.</p> <p>We are looking for a highly curious, product-minded Data Engineer I to join our Payment Lifecycle Data team in Amsterdam. Embedded within the Payments Core Data organization, our team builds foundational data products spanning all payment methods over the complete lifecycle of a payment.</p> <p>In this role, you will work directly with the product and engineering teams creating and managing global payment methods and services. You will take data initiatives from initial business requirements through pipeline implementation, stakeholder validation, and end-user adoption, shaping how data informs key product decisions across the entire Adyen platform.</p> <p><strong>What You’ll Do:</strong></p> <ul> <li><strong>End-to-End Data Product Ownership:</strong> Translate business questions into technical data solutions. You will help scope, design, build, and validate data products alongside product managers and engineers, gradually taking on more autonomy as you grow.</li> <li><strong>Build &amp; Maintain ETL Pipelines: </strong>Help design, build, and operate high-quality production ETL pipelines and data architectures on our Big Data Platform using Python, Pyspark and SQL.</li> <li><strong>Stakeholder Collaboration:</strong> Engage directly with internal stakeholders (such as software engineers, data analysts, and product owners) to understand data needs, clarify requirements, and ensure high adoption of our data products.</li> <li><strong>Ensure High Data &amp; Code Quality:</strong> Write clean, maintainable, and well-tested code. Implement testing, monitoring, and validation protocols using modern engineering tools to keep our payment data accurate, reliable, and timely.</li> <li><strong>Learn &amp; Modernise:</strong> Work alongside experienced Data Engineers to optimize data workflows, adopt modern developer tooling (including AI coding tools), and apply best practices in data governance, data modeling, and performance.</li> </ul> <p><strong><br>Who You Are:</strong></p> <ul> <li><strong>Educational Background:</strong> Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Science, Econometrics, or a related quantitative/data discipline.</li> <li><strong>Prior Experience: </strong>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).</li> <li><strong>Core Technical Fundamentals: </strong>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).</li> <li><strong>Product Mindset:</strong> 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 actually use.</li> <li><strong>Curiosity:&nbsp;</strong>You have a genuine passion for data engineering and continuous learning, supported by a supportive team ready to mentor your technical ramp-up.</li> </ul> <p><strong>Nice-to-Haves (Bonus):</strong></p> <ul> <li>Exposure to distributed data processing frameworks like PySpark or Spark.</li> <li>Prior experience with l