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- Tasks: Join us as an Analytics Engineer to build and optimise our data models and infrastructure.
- Company: Relay is revolutionising e-commerce logistics with a focus on sustainability and community impact.
- Benefits: Enjoy generous equity, performance bonuses, hybrid working, and 25 days' annual leave.
- Why this job: Be part of a fast-growing startup that values innovation and collaboration in a dynamic environment.
- Qualifications: Strong SQL skills, experience with data models, and a STEM degree or equivalent experience required.
- Other info: Work in a dog-friendly office with regular team socials and access to cutting-edge AI tools.
The predicted salary is between 43200 - 72000 £ per year.
Company Mission
In the future, commerce will be instant, local, and seamless. What we now call \”e-commerce\” will simply be
Company Mission
In the future, commerce will be instant, local, and seamless. What we now call \”e-commerce\” will simply be how we shop.
Relay is building the logistics network that e-commerce should have had from the start. We\’re designed from the ground up for sustainability – environmental, social, and economic. By rethinking both the middle and last mile, we cut miles driven, reduce carbon emissions, lower costs, and return value to local communities.
Behind the scenes, we orchestrate this with cutting-edge tech: from smart routing and real-time planning to seamless tools that empower our ground teams.
We’re not just building the future, we\’re scaling it fast.
- We just closed a $35M Series A, the largest ever for a logistics tech startup in Europe.
- Brands like Vinted, TikTok, and Temu are choosing Relay to power their UK expansion.
- We\’re growing at a top 0.01% among all European Series A startups.
Role Overview
As a highly operational business, we rely on data science to guide how every parcel moves through our network — from when it enters the system to when it’s delivered at the doorstep.
We’re looking for an exceptional Analytics Engineer to help us build our data foundations. In this role, you will:
- Partner closely with engineers and business leaders to design and build Relay’s core data models
- Work with Senior and Lead Analytics Engineers to take ownership of Relay’s data infrastructure, including our ingestion, ETL, data quality monitoring and data catalogue.
- Collaborate with team members across every function and business area at Relay.
- Regularly spend time in the field understanding how your data models match the on-the-ground reality for our couriers and end-consumers.
What You’ll Do
- You’ve contributed to maintaining or improving a data warehouse or core data models for an operational team or product area.
- You’re excited by fast-paced environments and are keen to learn what good looks like as part of an experienced data team.
- You’re a reliable and proactive collaborator, eager to build your skills and contribute to shared team goals.
- You are organised, detail-oriented, and comfortable juggling multiple tasks in a startup setting.
- You are naturally curious, enjoy solving problems, and are looking for opportunities to grow your technical and business understanding.
Who You Are
- Strong SQL skills, with hands-on experience in BigQuery or PostgreSQL; confident working with moderately complex data transformations
- Have contributed to dbt models in production and understand principles of modular, testable, and reliable DAGs
- Proficient in Python for data cleaning, scripting, or light automation; comfortable navigating notebooks and writing reusable code
- Experience using tools like Tableau (or similar) to support stakeholders with clean, accurate dashboards and analysis
- Communicate clearly with both technical and non-technical teammates; comfortable gathering requirements and flagging trade-offs
- 3+ years in data, analytics, or engineering roles with demonstrated impact
- Hold a STEM degree or equivalent experience, and bring a strong appetite for learning and taking on complex problems
Nice To Haves
- Have experience with orchestration tools like Dagster or similar.
Relay is offering
- Generous equity package
- Performance bonus in the form of equity
- High-performance culture with 2 promotion windows per year
- 25 days\’ annual leave, plus bank holidays
- Bupa Global Business Premier health plan – including mental, dental, and optical cover
- Enhanced Parental Leave
- Contributory pension scheme
- Friday office lunches
- Access to cutting-edge AI tooling
- Hybrid working from our dog-friendly Shoreditch office
- Free gym membership via our co-working spaces
- Cycle-to-work scheme
- Regular team socials, events, and offsites!!
Seniority level
-
Seniority level
Mid-Senior level
Employment type
-
Employment type
Full-time
Job function
-
Job function
Information Technology
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Industries
Consumer Services
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Analytics Engineer employer: Relay Technologies
Contact Detail:
Relay Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer
✨Tip Number 1
Familiarise yourself with Relay's mission and values. Understanding their focus on sustainability and local communities will help you align your answers during interviews, showcasing how your personal values resonate with theirs.
✨Tip Number 2
Brush up on your SQL skills, especially with BigQuery or PostgreSQL. Since strong SQL skills are a must for this role, being able to demonstrate your proficiency in these areas during discussions can set you apart from other candidates.
✨Tip Number 3
Prepare to discuss your experience with data models and ETL processes. Be ready to share specific examples of how you've contributed to data infrastructure in previous roles, as this will highlight your hands-on experience and problem-solving abilities.
✨Tip Number 4
Network with current employees or alumni who work at Relay. Engaging with them can provide valuable insights into the company culture and expectations, which can be beneficial when tailoring your approach during the interview process.
We think you need these skills to ace Analytics Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering and analytics. Focus on your SQL skills, experience with BigQuery or PostgreSQL, and any contributions to dbt models. Use specific examples that demonstrate your impact in previous roles.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for Relay's mission and how your skills align with their needs. Mention your experience in fast-paced environments and your ability to collaborate across teams. Show that you understand the importance of data in logistics.
Showcase Technical Skills: Be explicit about your technical skills in your application. Highlight your proficiency in Python for data cleaning and automation, as well as your experience with tools like Tableau. If you have experience with orchestration tools like Dagster, make sure to include that too.
Demonstrate Problem-Solving Ability: Relay values curiosity and problem-solving skills. In your application, provide examples of challenges you've faced in previous roles and how you approached them. This will show your potential to grow and contribute to their team effectively.
How to prepare for a job interview at Relay Technologies
✨Showcase Your SQL Skills
Make sure to highlight your strong SQL skills during the interview. Be prepared to discuss your experience with BigQuery or PostgreSQL, and share specific examples of how you've handled complex data transformations in past projects.
✨Demonstrate Your Collaboration Skills
Relay values teamwork, so be ready to talk about how you've partnered with engineers and business leaders in previous roles. Share instances where your collaboration led to successful outcomes, especially in fast-paced environments.
✨Prepare for Technical Questions
Expect technical questions related to dbt models and Python scripting. Brush up on your knowledge of modular, testable DAGs and be ready to explain how you've used Python for data cleaning or automation tasks.
✨Understand the Business Context
Familiarise yourself with Relay's mission and how data impacts their operations. Be prepared to discuss how your data models can align with real-world logistics challenges, showing that you understand both the technical and business aspects of the role.
