At a Glance
- Tasks: Design and implement data models to drive insights and analytics across the organisation.
- Company: Join a leading fintech company focused on innovation and data-driven decisions.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and continuous improvement.
- Why this job: Make a real impact by optimising analytics workflows and shaping data strategies.
- Qualifications: Experience in data modelling, SQL, and cloud technologies like Snowflake or AWS.
The predicted salary is between 50000 - 70000 £ per year.
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.
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.
- Own end‑to‑end responsibility for multiple data products from design to implementation to operationalisation.
Key Requirements
- Proven delivery experience as a data, business intelligence or analytics engineer.
- Hands‑on proven data modeling 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 (ideally proficient in dbt or similar).
- Familiarity with at least one cloud technology: Snowflake, AWS, Google Cloud, or Microsoft Azure.
- Passionate about sales, finance, customer, marketing and/or product analytics data.
- Good attention to detail to highlight and address data quality issues.
Analytics Engineer employer: 0026 Checkout Technology Ltd
At Checkout, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As an Analytics Engineer, you'll have access to cutting-edge tools and technologies, alongside ample opportunities for professional growth and development in a supportive environment. Our commitment to employee well-being is reflected in our flexible working arrangements and a strong focus on work-life balance, making Checkout a truly rewarding place to advance your career.
Contact Details:
0026 Checkout Technology Ltd Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data models and analytics projects. This is your chance to demonstrate your hands-on experience with tools like dbt and Snowflake, making you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and data transformation skills. Be ready to discuss your past projects and how you've tackled data quality issues. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications come directly from passionate candidates. Plus, it gives you a better chance to showcase your enthusiasm for the role.
We think you need these skills to ace Analytics Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Analytics Engineer role. Highlight your experience with data modelling, SQL skills, and any relevant projects you've worked on. We want to see how your background aligns with what we're looking for!
Showcase Your Projects:Include specific examples of your work in analytics engineering. If you've designed data models or implemented Looker structures, let us know! This helps us understand your hands-on experience and how you can contribute to our team.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to read. We appreciate a well-structured application that gets straight to the important bits!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to track your application status directly. Plus, we love seeing applications come through our own platform!
How to prepare for a job interview at 0026 Checkout Technology Ltd
✨Know Your Data Tools
Make sure you brush up on your SQL skills and get familiar with dbt and Snowflake. Be ready to discuss how you've used these tools in past projects, as they'll want to see your hands-on experience.
✨Understand the Business Impact
Get a good grasp of how analytics can drive business decisions. Think about how your work as an Analytics Engineer can influence sales, finance, or marketing strategies. Be prepared to share examples of how you've done this before.
✨Showcase Your Collaboration Skills
Since you'll be working closely with data analysts and business teams, highlight your teamwork experiences. Share specific instances where you’ve collaborated to meet business requirements and how you ensured the data was ready for analysis.
✨Emphasise Quality and Governance
Be ready to talk about your approach to data quality and governance. Discuss any best practices you follow for testing, documentation, and peer reviews. This shows that you take ownership of your data products seriously.
