Senior Analytics Engineer
AI in this role
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
As a Data Analytics Engineer at Checkout you will be responsible for enabling key insights on how products are performing and establishing a single source of truth for North Star and tracking metrics, working closely with product managers and product data scientists to shape the product’s evolution at Checkout.
You'll have the opportunity to build new data products and introduce step changes in how we view analytics for these critical areas. You'll have end-to-end ownership of multiple data products from design to implementation to the operationalisation.
How You’ll Make An Impact
Design and implement high-performance, reusable, and scalable data models for our data warehouse using dbt and Snowflake
Design and implement Looker structures (explores, views, etc) which will enable users across the organization to self-serve analytics
Work closely with data analysts and business teams to understand business requirements and provide data ready for analysis and reporting
Continuously discover, transform, test, deploy and document data sources and data models
Apply, help define, and champion data warehouse governance: data quality, testing, documentation, coding best practices and peer reviews
Take initiative to improve and optimise analytics engineering workflows and platforms
Key Requirements
Proven delivery experience as a data, business intelligence or analytics engineer
Hands-on proven data modelling and data warehousing skills demonstrated in large-scale data environments
Proven experience in software development lifecycle in analytics (e.g. version control, testing, and CI/CD)
Excellent SQL and data transformation skills (e.g. ideally proficient in dbt or similar)
Familiarity with at least one of these Cloud technologies: Snowflake, AWS, Google Cloud, Microsoft Azure
Passionate about sales, finance, customer, marketing and/or product analytics data
Good attention to detail to highlight and address data quality issues
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
How we rate this
Senior Analytics Engineer at Checkout.com rates 21 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
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