Data Infrastructure Engineer

Strategy – Business Intelligence
Permanent Full-time
About us

Launched in 2012, is a leading international provider of online payment solutions. is built on 100% proprietary technology and handles every part of the payment process, providing complete transparency across the entire payment value chain.

We currently process 150+ currencies and offer access to all international cards and popular local payment methods to merchants through one integration.

Customers in our portfolio include international businesses like Samsung, Transferwise, Hopper, Virgin and Adidas. Our mission is to partner with smart businesses to optimise their payments, increase revenue and meet the dynamic needs of their customers. 

We are building a unique work environment where our people aspire to solve complex problems and deliver valuable solutions. We believe that excellence can be achieved through a dynamic culture driven by collaboration and teamwork.

In May 2019, we raised $230m in what is Europe’s largest ever fintech Series A round, and globally the third largest fintech Series A round of all time. This fundraising round gave us a valuation of around $2 billion.

About the Role is looking for an ambitious engineer who will join our BI Data Team and work with data science to design and implement high-performance data infrastructure. This infrastructure will be used for:
- Training, deploying, and monitoring machine learning models
- Providing real-time transaction fraud predictions for our merchants
To do this, familiarity with event-driven architecture and stream processing technologies is expected.

Key Responsibilities

    • Work with stream processing technologies (e.g. Kinesis, Kafka) to build a platform which processes transaction data in real-time
    • Design and implement infrastructure to train, deploy and monitor machine learning models
    • Support Data Scientists by building libraries and tooling that provide elegant, easy to use, abstractions

About You

    • Strong engineering background with an interest in data and machine learning
    • Creative problem solver with strong attention to detail
    • Experience working with stream processing (e.g. Kinesis, Kafka)
    • Familiar with distributed cluster-computing (e.g. Spark, Dask, Hadoop)
    • Experience working with AWS (Kinesis, Lambda, EMR)
    • Extensive experience with SQL databases and key-value stores (NoSQL)
    • Able to write high quality, production-ready, Python code
    • Understanding of HTTP and RESTful design
    • Experience working with Docker, and container deployment
    • Familiar with the unix shell, and shell scripting (for automating tasks)

and the "nice to have"

    • Experience building high-performance (high-throughput / low-latency) data products or machine learning systems
    • Experience with continuous integration and deployment workflowsFamiliarity with task scheduling technologies (e.g. Airflow, Metaflow)
    • Data warehousing experience (e.g. Snowflake)
    • Open source contributions and/or personal software projects
    • Experience with C# and/or Scala
    • Academic background in STEM is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience, skills and personality. We welcome applications from all members of society irrespective of age, sex, disability, sexual orientation, race, religion or belief. Due to the numerous amount of application received, only the ones corresponding to this job profile will be contacted. If you have not been contacted within 3 weeks please deem your application as unsuccessful.

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