Senior Data Engineer
Adyen is a financial technology company providing a unified platform for payments, data, and financial products. It serves global enterprises, retailers, platforms, marketplaces, and other high-growth businesses.
Projects
About Adyen
Adyen provides payment processing and financial technology services through a single platform. Its offerings include online and in-person payments, payment methods, risk management, authentication, revenue optimization, issuing, payouts, liquidity management, embedded accounts, and capital. Adyen typically serves global enterprises, retailers, SaaS platforms, marketplaces, and other high-growth businesses.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You design, develop, deploy, and operate production ELT pipelines and data architectures on a Big Data Platform. You integrate diverse data sources, establish engineering and governance practices, ensure data quality, optimize performance, and collaborate with stakeholders across technical and business functions.
Requirements
- Over 7 years of experience as a Data Engineer or in a similar role
- Expert-level Software Engineering and Data Engineering practices
- Proficiency in Python, PySpark, Airflow, Hadoop, Spark, Kafka, SQL, and Git
- Ability to communicate complex data concepts to diverse stakeholders
- Experience establishing data standards and fostering a data-centric culture
- Testing and validation experience with tools such as Pytest
Responsibilities
- Engage stakeholders to understand requirements and develop solutions
- Design, develop, deploy, and operate production ELT pipelines
- Design scalable data architectures
- Integrate data from varied sources and formats
- Establish and advocate for performance, code quality, validation, governance, and discoverability practices
- Mentor, train, and share knowledge
- Ensure data accuracy, completeness, reliability, relevance, and timeliness
- Implement testing, monitoring, and validation protocols
- Identify and resolve pipeline and system performance bottlenecks
- Optimize queries and resource utilization with caching, indexing, partitioning, and Spark optimizations