This is Adyen
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.
Sitting at the intersection of Data Engineering, Backend Engineering, and Systems Engineering, Data Platform Engineers at Adyen build the foundational layer of tooling and processes for our on-premise Big Data Platforms. These tools support 10s of products, 100s of developers, and 1000s of daily jobs that add to Adyen's strong portfolio of capabilities.
You'll collaborate with data engineers and ML scientists and engineers to build and roll-out these tools. Along with DataOps Engineers, you'll develop and operate multiple big data platforms, of which the biggest is 500+ nodes, with 25k+ CPU cores, 240+ TBs of RAM, and 23+ PBs of storage capacity, running tens of thousands of spark jobs a day.
What you'll do
You'll be asked to both build new tools and improve the existing tooling. This role is perfect for you if you're passionate about few of the following:
- Develop and maintain scalable and high performance big data platforms.
- Work with distributed systems in all shapes and flavors (databases, filesystems, compute, etc.)
- Identify opportunities to improve continuous release and deployment environments
- Build or deploy tools to enhance data discoverability through the collection and presentation of metadata
- Introduce and extend tools to enhance the quality of our data, platform-wide
- Explore and introduce technologies and practices to reduce the time to insight for analysts and data scientists
- Develop streaming processing applications and frameworks
- Experience in infrastructure and large-scale private cloud systems
Who you are
- At least 6+ years experience with Python object oriented programming.
- Team player with strong communication skills
- Ability to work closely with diverse stakeholders you enable (analysts, data scientists, data engineers, etc.) and depend upon (infrastructure, security, etc).
- Experience developing and maintaining:
- Distributed data and compute systems like Spark, Trino, Druid, etc
- Data modelling tooling
- DevOps pipelines and development ecosystems.
- Real-time and batch data pipelines (via Kafka, Spark streaming) with an eye for frameworks, and emphasis on user friendliness and quality.
- Kubernetes ecosystem (k8s, docker), and/or Hadoop ecosystems (Hive, Yarn, HDFS, Kerberos).
Our Diversity, Equity and Inclusion commitments
Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours. No matter who you are or where you're from, we welcome you to be your true self at Adyen.
Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application!
What's next?
Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don't be afraid to let us know if you need more flexibility.
This role is based out of our Amsterdam office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.
