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Checkout.com

Data Analytics Engineer I

London
Posted 1 day ago
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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.

Role Description

You will be joining the Financial Infrastructure team, responsible for building and maintaining the core systems powering our internal financial ecosystem. Every year, we process hundreds of billions of events that have a financial impact on Checkout.com and our merchants. Our team is responsible for maintaining an accurate record of all financial data, the data integrity of our systems and ensuring our infrastructure meets regulatory and compliance obligations in a scalable, reliable and fault-tolerant manner.

As an Analytics Engineer, you will play a pivotal role in our mission to make our financial data capabilities world-class. You will work closely with our Finance and Treasury teams to translate their requirements into robust and intuitive data models. You will design and build the data pipelines necessary to process and transform large amounts of data that our systems generate. You will be responsible for ensuring the accuracy and reliability of these data pipelines, as Checkout continues to scale as a business. You will have ownership over these processes, allowing you to take charge in maintaining a high standard of data quality.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

Only hits

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How You’ll Make An Impact

  • Design and build data pipelines to process data from our systems, services and applications.
  • Implement monitoring and alerting frameworks to ensure data pipeline performance and reliability.
  • Partner with other analytics engineers to design and implement scalable data models that support downstream business operations and analytical queries.
  • Ensure data governance and security standards are maintained across our systems.
  • Continuously evaluate and implement new technologies to improve our platform and systems.
  • Collaborate with Finance stakeholders to translate business requirements into technical specifications and Service Level Agreements.

Qualifications

  • 2+ years of experience in an Analytics Engineering or Data Engineering role with a focus on large scale data transformation and data warehousing.
  • Excellent SQL coding skills.
  • Experience with cloud-based data warehouse technologies such as Snowflake, Google BigQuery, or AWS Redshift.
  • Experience with data transformation tools such as dbt, or Dataflow.
  • Understanding of data modeling techniques.
  • Experience with using visualisation platforms such as Looker, Tableau, or Apache Superset.
  • Understanding of software engineering best practices and their application to data processing systems.
  • Knowledge of Python, Java or Flink is a plus, but not a necessity.
  • Strong attention to detail.
  • Ability to work autonomously in a fast-paced and dynamic environment.
  • Strong communication and interpersonal skills.

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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.

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Skills

SQL
Data Engineering
Data Modeling
Snowflake
Google BigQuery
AWS Redshift
Dbt
Dataflow
Looker
Tableau
Apache Superset
Python
Java
Flink
Data Governance
Data Pipelines

Location

London, England, United Kingdom

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