Level

Checkout.com

Staff Software Engineer - Streaming

AI in this role

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.

Job Description

About the role

Checkout.com is looking for an ambitious Staff Data Engineer to join our Data and AI Platform Team. Our team’s mission is to build a platform where you can create reliable, scalable, AI-powered streaming and batch data applications, and share data across Checkout.com to improve business performance.


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

We're building for scale. As such, much of what we design and implement today is the technology/infrastructure which will serve hundreds of teams and petabyte-level volumes of data.

Key Responsibilities

  • Work with stream processing technologies (Kafka and Flink) to build a continuously available large-scale event streaming platform

  • Leverage subject matter and technical expertise to provide leadership, mentoring, and strategic influence across the organisation whilst building strong relationships with engineers and engineering managers

  • Build tooling (modules/SDKs/DSLs) and associated documentation to foster the adoption of the streaming platform by enabling upstream teams and systems to easily publish data and deploy streaming applications

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

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

  • Participate, translate, run and execute the collection of requirements and architecture/design initiatives into action plans

  • Provide hands-on support for all event-based systems including incident triage and root cause analysis


About You

While experience with our specific tech stack is a plus, we welcome candidates with a strong background in data systems who are eager to learn. The core remit of this role is to own and scale our event streaming capability, not to serve as a general DevOps or infrastructure engineer.

  • Strong presentation and communication skills with a proven track record of influencing engineering organisations

  • Strong engineering background with a track record of implementing and owning event streaming platforms

  • Hands-on experience working with stream technologies, ideally Kafka

  • Experience designing and implementing stream processing applications with Flink

  • Experience working with cloud-based technologies such as AWS (MSK, S3, Lambda, ECS, SNS)

  • Experience with Kubernetes (either self-hosted or on the cloud)

  • Experience with SQL databases

  • Experience working with Docker, container deployment and management

  • Experience describing infrastructure as code (Terraform or similar) as well as designing and implementing CI/CD pipelines

  • Excellent programming skills with at least one of Java or Python

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 at Checkout.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 our Careers 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

How we rate this

Staff Software Engineer - Streaming at Checkout.com rates 22 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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