checkout.com - BigQuery Data Engineer
Requirements
• 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 • 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 • 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 http://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 https://www.checkout.com/careers to learn more about our culture, open roles, and what drives us. • For a closer look at daily life at Checkout.com http://Checkout.com, follow us on LinkedIn https://www.linkedin.com/company/checkout/life/ and Instagram https://www.instagram.com/checkout_com/
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
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