At a Glance
- Tasks: Build and maintain dbt models for analytics, transforming raw data into high-quality datasets.
- Company: Join a $220M Series D EdTech unicorn valued at $1.7bn.
- Benefits: Enjoy 32+ days of annual leave, hybrid work, and a culture of engineering excellence.
- Other info: Work in a high-growth environment with opportunities for career advancement.
- Why this job: Be part of a mission-driven team equipping the global workforce for the AI era.
- Qualifications: 2+ years in SQL and dbt models, with expertise in data warehouse design.
The predicted salary is between 60000 - 80000 £ per year.
You will build and maintain the dbt models powering analytics across the business. Reporting to the Director of Data Engineering, you’ll transform raw data into high-quality datasets on Snowflake, ensuring data is accessible and trusted. This is a technical role focused on dimensional modelling, robust CI/CD pipelines, and driving AI adoption through clean data.
Location: London, UK
Why this role is remarkable:
- Join the UK’s first EdTech unicorn on a mission to equip the global workforce for the AI era, having already driven £2bn+ in ROI for 1,500+ partner companies.
- Work in a high-growth environment backed by $220M in funding, where your data models serve as critical infrastructure for 800+ employees and millions in revenue.
- Benefit from a culture that values engineering excellence, offering a hybrid model, 32+ days of annual leave, and dedicated work‑from‑anywhere flexibility.
What You Will Do:
- Design and implement scalable data models and warehouse schemas using Kimball-style dimensional modelling techniques within a Snowflake data lake environment.
- Build, test, and document production‑grade dbt models to transform complex business logic into clean, accessible datasets for analysts and data scientists.
- Manage the evolution of the data platform by maintaining CI/CD pipelines, performing code reviews, and exposing metrics through a Semantic Layer like Looker or Cube.
The ideal candidate:
- Has 2+ years of experience building and optimising complex SQL and production dbt models, including a strong grasp of window functions and performance tuning.
- Demonstrates deep expertise in data warehouse design and dimensional modelling (fact/dimension tables, SCDs) to support cross‑functional analytics requirements.
- Is comfortable working in a modern engineering workflow involving GitHub, CI/CD, and ideally has exposure to Python/Airflow or Snowflake‑based architectures.
Analytics Engineer at $220M Series D EdTech unicorn employer: Jack & Jill
Join a pioneering EdTech unicorn in London, where you will play a vital role in shaping the future of workforce education for the AI era. With a strong emphasis on engineering excellence, our culture promotes innovation and collaboration, offering generous benefits such as 32+ days of annual leave and flexible working arrangements. As part of a high-growth team backed by significant funding, you'll have ample opportunities for professional development and to make a meaningful impact across the organisation.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer at $220M Series D EdTech unicorn
✨Tip Number 1
Network like a pro! Reach out to current employees at the company on LinkedIn. A friendly message can go a long way in getting your foot in the door and showing your genuine interest in the role.
✨Tip Number 2
Prepare for the technical interview by brushing up on your SQL and dbt skills. We recommend doing some mock interviews with friends or using online platforms to get comfortable with the types of questions you might face.
✨Tip Number 3
Showcase your projects! If you've built any data models or worked on relevant projects, make sure to have them ready to discuss. This is your chance to demonstrate your hands-on experience and problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining our mission in the EdTech space.
We think you need these skills to ace Analytics Engineer at $220M Series D EdTech unicorn
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Analytics Engineer role. Highlight your experience with SQL, dbt models, and any relevant projects that showcase your data modelling expertise.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're excited about joining StudySmarter. Share specific examples of how your background aligns with our mission and the technical requirements of the role.
Showcase Your Technical Skills:Don’t shy away from detailing your technical skills in your application. Mention your experience with Snowflake, CI/CD pipelines, and any tools like GitHub or Looker that you’ve used. We love seeing candidates who can demonstrate their technical prowess!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Jack & Jill
✨Know Your Data Modelling Inside Out
Make sure you brush up on dimensional modelling techniques, especially Kimball-style. Be ready to discuss your experience with fact and dimension tables, as well as slowly changing dimensions (SCDs). This will show that you understand the core of what the role entails.
✨Show Off Your SQL Skills
Prepare to demonstrate your SQL prowess during the interview. Have examples ready where you've optimised complex queries or built production-grade dbt models. Being able to talk through your thought process will impress the interviewers.
✨Familiarise Yourself with CI/CD Pipelines
Since this role involves maintaining CI/CD pipelines, make sure you can explain how you've used these in past projects. Discuss any tools you've worked with, like GitHub, and how you've managed code reviews. This will highlight your technical workflow experience.
✨Emphasise Your Adaptability to New Technologies
The company is focused on driving AI adoption, so be prepared to discuss how you've adapted to new technologies in your previous roles. If you have experience with Python, Airflow, or Snowflake, make sure to mention it and how it can benefit their data platform.
