At a Glance
- Tasks: Design and maintain scalable analytics models to empower data-driven decisions.
- Company: Join Just Eat, a leading global online food delivery marketplace.
- Benefits: Hybrid work model, competitive salary, and a vibrant team culture.
- Other info: Dynamic environment with opportunities for growth and collaboration.
- Why this job: Make an impact by transforming data into insights that drive innovation.
- Qualifications: Strong SQL skills and experience with dbt and cloud data warehouses.
The predicted salary is between 50000 - 65000 £ per year.
hackajob is collaborating with Just Eat to connect them with exceptional professionals for this role. Ready for a challenge? That’s good, because at Just Eat Takeaway.com (JET) we have abundant opportunity, or, as we say, everything is on the table. We are a leading global online food delivery marketplace. Our tech ecosystem connects millions of active customers with hundreds of thousands of connected partners in countries across the globe. Our mission? To empower every food moment around the world, whether it’s through customer service, coding or couriers.
About This Role
We are looking for a passionate Analytics Engineer to join our Retail Media Insights & Enablement team. This team plays a key role in shaping the semantic data layer that powers Retail Media analytics, experimentation, and data-driven product development. As part of a multidisciplinary team including data engineers, data scientists, ML engineers, and analysts, you will design and maintain trusted analytics models and reusable datasets that power dashboards, internal tools, experimentation platforms, and emerging AI-driven analytics workflows. You’ll also partner with the broader Product & Tech department, helping scale capabilities across our wider engineering teams.
We’re seeking problem-solvers, who are passionate about data quality, scalable infrastructure, and empowering business users with reliable information. You will transform raw advertising and customer data into reliable, well-structured data products that support campaign optimisation, advertiser insights, and product innovation across Retail Media.
Location: Hybrid – 3 days a week from JET’s London office & 2 days working from home.
These are some of the key components to the position:
- Design and maintain scalable analytics models and semantic datasets that act as the source of truth for Retail Media metrics.
- Build modular data transformations using dbt and SQL following analytics engineering best practices.
- Define and maintain core business metrics such as campaign performance, conversion rates, and ROAS.
- Develop and maintain reliable data pipelines and workflows using orchestration tools such as Airflow.
- Ensure data quality through testing, monitoring, and CI/CD practices using Git-based workflows and GitHub Actions.
- Collaborate closely with data scientists, ML engineers, analysts and product teams to support experimentation and modelling.
- Enable scalable data consumption across dashboards, applications, and machine learning systems.
- Contribute to shared standards, documentation, and best practices within the broader JET data community.
- Create and maintain data workflows using modern tools like Airflow and dbt.
- Experienced and/or open to using Agentic tools like co-pilot, cursor, kiro or codex.
- Contribute to shared tools, documentation and best practices in the wider data engineering and analytics community at JET.
What will you bring to the team?
- Strong SQL skills and experience designing scalable analytics data models.
- Hands‑on experience with dbt for production data transformations.
- Production experience with a modern transformation tool, specifically dbt.
- Experience working with modern cloud data warehouses with Amazon Redshift and/or Google BigQuery.
- Strong grasp of software engineering principles including version control (Git) and testing methodologies in a data environment.
- Demonstrated experience orchestrating pipelines using tools such as Apache Airflow.
- Understanding of data quality, testing and monitoring practices in analytics environments.
- Experience connecting data models to and supporting users of visualization platforms (i.e. Tableau, Looker Studio or Quicksight).
- A collaborative mindset, eager to learn and share knowledge with peers while providing ongoing support to users.
- Experience with programming languages like Python.
Nice To Have
- Experience working with advertising or Retail Media datasets.
- Experience supporting experimentation or A/B testing platforms.
- Experience with large‑scale event data.
- Exposure to semantic layers or metrics frameworks.
At JET, This Is On The Menu
Our teams forge connections internally and work with some of the best‑known brands on the planet, giving us truly international impact in a dynamic environment. Fun, fast‑paced and supportive, the JET culture is about movement, growth and about celebrating every aspect of our JETers. Thanks to them we stay one step ahead of the competition.
Inclusion, Diversity & Belonging
No matter who you are, what you look like, who you love, or where you are from, you can find your place at Just Eat Takeaway.com. We’re committed to creating an inclusive culture, encouraging diversity of people and thinking, in which all employees feel they truly belong and can bring their most colourful selves to work every day.
What else is cooking?
Want to know more about our JETers, culture or company? Have a look at our career site where you can find people's stories, blogs, podcasts and more JET morsels.
Analytics Engineer in London employer: hackajob
Contact Detail:
hackajob Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Just Eat on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your SQL and dbt skills. Be ready to showcase how you've used these tools in real projects. We want to see your problem-solving skills in action!
✨Tip Number 3
Show your passion for data! During interviews, share examples of how you've transformed raw data into actionable insights. This will demonstrate your fit for the Analytics Engineer role at JET.
✨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 the JET team.
We think you need these skills to ace Analytics Engineer in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Analytics Engineer role. Highlight your SQL skills, experience with dbt, and any relevant projects that showcase your data modelling expertise. We want to see how you fit into our team!
Show Your Passion for Data: In your application, let us know why you're passionate about data quality and analytics. Share examples of how you've tackled data challenges in the past or how you've contributed to data-driven projects. We love seeing that enthusiasm!
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points where possible to make your skills and experiences stand out. We appreciate a well-structured application that’s easy to read!
Apply Through Our Website: Don’t forget to submit your application through our official website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, you’ll find more info about our culture and values there!
How to prepare for a job interview at hackajob
✨Know Your SQL Inside Out
As an Analytics Engineer, strong SQL skills are a must. Brush up on your SQL queries and be ready to discuss how you've used them in past projects. Prepare to explain your thought process when designing scalable analytics models.
✨Familiarise Yourself with dbt
Since you'll be using dbt for data transformations, make sure you understand its core functionalities. Be prepared to share examples of how you've implemented dbt in your previous roles, focusing on best practices and any challenges you overcame.
✨Showcase Your Collaboration Skills
This role involves working closely with data scientists, ML engineers, and product teams. Think of specific instances where you've collaborated effectively in a team setting. Highlight how you contributed to shared goals and supported your peers.
✨Prepare for Technical Questions
Expect technical questions about data pipelines, orchestration tools like Airflow, and data quality practices. Review common scenarios and be ready to discuss how you would approach problem-solving in these areas, demonstrating your analytical mindset.