At a Glance
- Tasks: Join our Data Platform Team to build and optimise a world-class data platform.
- Company: Checkout.com powers payments for major brands like eBay and Spotify.
- Benefits: Flexible hybrid working, real ownership, and opportunities for personal growth.
- Other info: Collaborative culture where your ideas and contributions are valued.
- Why this job: Make a real impact in fintech while working with cutting-edge technologies.
- Qualifications: Strong engineering background and experience with cloud data warehousing, especially BigQuery.
The predicted salary is between 60000 - 80000 £ per year.
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. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale.
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.
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
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.
Key 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
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.
Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection.
For a closer look at daily life at Checkout.com, follow us on LinkedIn and Instagram.
BigQuery Data Engineer in London employer: Checkout.com
Checkout.com is an exceptional employer that champions a flexible hybrid working model, allowing employees to balance their professional and personal lives effectively. With a strong emphasis on growth and collaboration, the company provides ample opportunities for career development while working alongside talented teams in the dynamic financial services sector in London. Joining Checkout.com means being part of a forward-thinking organisation that values compliance and innovation in payments and product regulation.
StudySmarter Expert Advice🤫
We think this is how you could land BigQuery Data Engineer in London
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We think you need these skills to ace BigQuery Data Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Checkout.com. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Checkout.com
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Checkout.com!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
