Data Engineer II
About The Position
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. 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. Data Engineer At Adyen, we treat data and data artifacts as first-class citizens. They form the backbone of our platform and power the business and product insights we deliver at scale. We are looking for a Data Engineer in Chicago to join our Developer Experience (DevX) team. In this role, you will be a key contributor to ensuring our merchants and partners experience a world-class platform integration. You will do this by building and maintaining reliable, high-quality data pipelines that enable data-driven decisions around developer behavior, integration friction, and platform performance - helping make integrating with Adyen not just easy, but a genuinely superior experience.
Requirements
- Experienced in Big Data: 3+ years of experience working as a Data Engineer or in a similar role.
- Data & Engineering practices: You have a solid understanding of both Software and Data Engineering practices.
- Technical Skills: Proficient in tools and languages such as: Python, PySpark, Airflow, Hadoop, Spark, Kafka, SQL, Git.
- Clear Communicator: Able to effectively communicate complex data-related concepts and outcomes to a diverse range of stakeholders.
- Self-starter: Capable of identifying opportunities, devising solutions, and handling projects independently.
- Innovator: You have an experimental mindset with a ‘launch fast and iterate’ mentality.
- Data Culture Champion: Skilled in promoting a data-centric culture within technical teams and advocating for setting standards and continuous improvement.
Responsibilities
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
