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Salary
$76k – $148k per year (Estimated)
Location
In office (London)
Seniority
Senior
Employment
Full-Time
Overview
Company
Impact
Profile match
Checkout.com is a London payments company founded in 2012 that processes card and alternative payments for large online merchants. It built a full stack acquiring and processing platform rather than assembling third party components, which lets it optimise authorisation rates directly. Its customers include marketplaces, streaming services and digital asset platforms across Europe, the Middle East and Asia.

Company Description

We’re Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day.

We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers.

Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale.

If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact.

With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech - and we’re just getting started.

Checkout.com is looking for an ambitious Data Engineer to join our Data Platform Team. Our team’s mission is to build a world-class data platform that powers our products and analytics.

The Data Platform team is here to ensure internal stakeholders can easily collect, store, process and utilise data to build reports or products aiming to solve business problems. Our focus is on maximising the amount of time business stakeholders spend on solving business problems and minimising time spent on technical details around implementation, deployment, and monitoring of their solutions.

The core tech stack we use is based on AWS and GCP, using:

  • Kafka as our message transport

  • Flink for (near) real time processing

  • Datahub as our catalog

  • BigQuery as our warehouse

  • Airflow (GCP Composer) for scheduling

  • DBT for data transformation

  • Montecarlo for monitoring

The platform here encompasses the end-to-end, first for real time / streaming use cases but also for our analytical / warehouse needs. We're building for scale. As such, much of what we design and implement today will be the technology/infrastructure which will serve hundreds of teams and petabyte-level volumes of data.

Key Responsibilities:

  • You’ll work as part of the team to build enablement components across the platform, as well as monitor and support the capabilities we offer.

  • Develop and maintain documentation for data systems and processes.

  • Participate in code and design reviews and provide constructive feedback.

  • Wherever possible, automate workflows and processes, we’re aiming for the platform to be as self-sustaining as possible.

  • Stay up-to-date with the latest data and streaming engineering technologies and trends.

  • Use that knowledge and subject matter expertise to mentor the more junior members of the team, and work with other “application” teams to provide guidance and best practice.

  • Build light weight tooling and associated reference patterns to foster the adoption of the platform by enabling upstream teams and systems to easily publish and manipulate data and deploy applications using industry best practices

  • Implement all the necessary infrastructure to enable end users to build, host, monitor and deploy their own applications

  • Provide consultancy across the technology organisation to drive the adoption of the platform and unlock use-cases

  • Promote data quality and governance as a first class citizen of the platform

Qualifications:

  • Strong engineering background with a track record of implementing and owning components of a data platform

  • Strong experience working with Cloud data warehousing technologies, in particular with BigQuery optimisation and FinOps

  • Experience working with modern cloud-based stacks such as AWS, Azure or GCP

  • Excellent SQL skills

  • Strong programming skills with at least one of Python, Java, Scala or C#

  • You’re a mentor, raising the bar for your colleagues.

  • You’re a collaborator, always ready to dive in and partner to solve tough problems.

  • You’re a listener, and seek to understand the underlying problems, before pitching solutions

  • You are able to drive through best practices by taking teams and organisations as a whole with you.

  • You are a thought leader, so we’d love to see articles, podcasts, meetups or conference talks if you’ve done them

Additional Information

Bring all of you to work

We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one.

Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity, and where your growth is in your hands.

We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here.

It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable.

Life atCheckout.com

We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection.

Curious about what it’s like to be part of our team? Visit ourCareers Page to learn more about our culture, open roles, and what drives us.

For a closer look at daily life at Checkout.com, follow us on LinkedIn and Instagram

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