Data Analytics Engineer I
Role Summary
Join Checkout.com as a Data Analytics Engineer I in London, specializing in building data pipelines and ensuring data integrity for financial systems.
About the Organisation
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.
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.
Minimum Requirements
- 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.
Eligibility Criteria
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