The opportunity
Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition.
What you'll do
Collaborative solution development: Engage with a diverse range of stakeholders, including data scientists, analysts, software engineers, product managers, and customers, to understand their requirements and craft effective solutions.
Quality pipelines and architecture: Design, develop, deploy and operate high-quality production ELT pipelines and data architectures. Integrate data from various sources and formats, ensuring compatibility, consistency, and reliability.
Data best practices: Help establish and share best practices in performance, code quality, data validation, data governance, and discoverability in your team and in other teams. Participate in mentoring and knowledge sharing initiatives.
High quality data and code: Ensure data is accurate, complete, reliable, relevant, and timely. Implement testing, monitoring and validation protocols for your code and data, leveraging tools such as Pytest.
Performance optimization: Identify and resolve performance bottlenecks in data pipelines and systems. Improve query performance and resource utilization to meet SLAs and performance requirements, using technologies Spark optimizations.
Technically proficient: Skilled in Data Engineering tools and languages such as Python, PySpark, Airflow, Hadoop, Spark, Kafka, SQL, Git .
What they're looking for
- Strategic executor: You excel at breaking down complex problems, prioritizing effectively, leading impactful projects, and aligning your work with strategic goals.
- Effective communicator: An excellent communicator in English who can deal with ambiguity, collaborate with diverse stakeholders, and translate complex insights for both technical and non-technical audiences in a global team.
- Curious and scalable mindset: You possess a curious mindset, with a continuous drive to iterate, improve, and find better, scalable solutions.
- Data culture champion: Skilled in promoting a data-centric culture within technical teams and advocating for setting standards and continuous improvement.
