Senior Data Engineer

Adyen•San Francisco, CA

5h•$198,000 - $293,000•Onsite

About The Position

We are seeking a high-impact Senior Data Engineer to join our Developer Experience (DevX) team in San Francisco. In this role, you will be the technical engine behind ensuring our merchants and partners experience a world-class platform integration. You are instrumental in building the scalable framework and high-reliability data sources that power intelligent insights, ensuring that integrating with our technology is not just easy, but a genuinely superior experience. You will live and breathe the technical framework that allows us to scale integration intelligence across our business partners. By architecting the framework and pipelines that surface proactive suggestions and collaborating with core development teams to maintain well-structured data sources, you will ensure our customer-facing products deliver reliable recommendations at scale. Ultimately, you will turn complex data into simple and understandable suggestions that make our technology intuitive and powerful for the developers who build on it.

Requirements

A Senior Data Engineer with 6+ years of experience, ideally in a fast-paced, product-focused setting, comfortable operating with significant autonomy.
Technically proficient: Skilled in Data Engineering tools and languages such as Python, PySpark, Airflow, Hadoop, Spark, Kafka, SQL, Git.
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.

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.