Staff Software Engineer - Streaming
Checkout.com LondonEst. Est. GBP 90,000–130,000 / yearLead
Estimated range based on role, country and industry — not published by the company.
Key requirements
- Python
- Java
- Sql
- Aws
- Kubernetes
- Docker
- Terraform
- Ci/Cd
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/C
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