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- Tasks: Join us as a Senior Analytics Engineer to build and optimise our data infrastructure.
- Company: RELAY is revolutionising logistics with cutting-edge technology and a vibrant team culture.
- Benefits: Enjoy generous equity, private health coverage, 25 days holiday, and awesome perks like gym subsidies.
- Why this job: Be part of a fast-growing startup that values innovation and teamwork while making e-commerce seamless.
- Qualifications: 5+ years in analytics or data engineering, strong SQL skills, and proficiency in Python required.
- Other info: Experience a fast-paced hiring process and work alongside industry leaders in a dynamic environment.
The predicted salary is between 48000 - 84000 £ per year.
Overview
Senior Analytics Engineer @ RELAY
Relay is fundamentally reshaping how goods move in an online era. Backed by Europe’s largest-ever logistics Series A ($35M), led by deep‑tech investors Plural (whose portfolio spans fusion energy and space exploration), Relay is scaling faster than 99.98% of venture-backed startups. We\’re assembling the most talent-dense team the logistics industry has ever seen.
The team
- ~90 people, more than half in engineering, product and data
- 45+ advanced degrees across computer science, mathematics and operations research
- Thousands of data points captured, calculated, analysed and predicted for every single parcel we handle
- An intellectually vibrant culture of first‑principles thinking, tight feedback loops and relentless experimentation
Work Alongside Industry Leaders
Andy Turner – Director of Data
Andy Turner has built and led data teams across global enterprises and high-growth scale-ups on five continents. He has delivered cloud native platforms, launched AI products end-to-end, and holds patents for novel machine learning applications in the UK Capital Markets. Trained in statistics at Oxford, he pairs strong technical fundamentals with clear judgement, a commercial focus, and a bias to deliver.
Relay’s Mission
Relay exists to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone.
In This Future
- Delivery feels invisible—free shipping is the default, and logistical friction disappears from consumers\’ minds.
- Retailers of all sizes thrive equally online, whether selling a £5 item or a £500 one, as delivery becomes universally efficient and cost-effective.
Just as the internet eliminates friction from communication, Relay removes friction from the movement of goods, enabling broader participation and creating new opportunities for merchants and consumers alike.
Tech Stack Highlights
- Cloud-native on GCP with extensive use of BigQuery and Cloud Run
- Extensive use of ML modelling and LLM inference – no gimmicks here, this is our daily routine
- Python, Rust and TypeScript – we keep things simple but use the right tool for the job
- Cross-platform Flutter apps with a deep focus on user experience
- Emerging tech integrations, including robotics and IoT-powered operations
The Opportunity
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 Senior 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
- 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
Who Will Thrive in this role?
- You’ve built and maintained the data warehouse for a fast-growing or highly operational line of business.
- You thrive in a dynamic company that is growing fast and are excited to join the team early, and help define our data best practices.
- You’re an independent and proactive team player, excited to learn from and share knowledge with others in the data team and wider business.
- You are highly organised, detail-oriented, and able to manage multiple projects and priorities in a challenging start-up environment.
- Demonstrable, in-depth experience with SQL, particularly in BigQuery and PostgreSQL.
- Proven experience with dbt, focusing on building and maintaining efficient, scalable, and reliable DAGs.
- Proficiency in Python for data manipulation, scripting, or automation tasks.
- Are proficient with data visualisation tools such as Tableau or similar.
- Excellent communication and people skills: you will be working closely with analysts and non-technical stakeholders to gather requirements and guide them to pick and choose the right data.
- 5+ years of experience as an analytics engineer or data engineer.
Who Thrives at Relay?
- Aim with Precision: You define problems clearly and measure your impact meticulously.
- Play to Win: You chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction.
- 1% Better Every Day: You believe that small, consistent improvements lead to exponential growth. You move quickly, deliver results, and learn from every experience.
- All In, All the Time: You show up and step up. You take ownership from start to finish and do what it takes to deliver when it counts.
- People-Powered Greatness: You invest in your teammates. You give and receive feedback with care and candour. You build trust through high standards and shared success.
- Grow the Whole Pie: You seek out win-win solutions for merchants, couriers, and our customers, because when they thrive, so do we.
Compensation & Benefits
- Generous equity, richer than 99% of European startups, with annual top-ups to share Relay’s success.
- Private health & dental coverage, so comprehensive you’d need to be a partner at a Magic Circle law firm to match it.
- 25 days of holidays
- Enhanced parental leave.
- Hardware of your choice.
- Extensive perks (gym subsidies, cycle-to-work, Friday office lunch, covered Uber home and dinner for late nights, and more).
Fast and Focused Hiring Process
- Talent Acquisition Interview – 30 min
- Hiring Manager Interview – 45mins
- SQL Live Coding – 60mins
- Architecture Design – 60mins
- Relay Operating Principles & Impact – 1 hour
- Decision and offer within 48 hours. Our process mirrors our pace of work.
Relay is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Seniority level
- Mid-Senior level
Employment type
- Full-time
Job function
- Information Technology
Industries
- Consumer Services
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Senior Analytics Engineer employer: Relay Technologies
Contact Detail:
Relay Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Analytics Engineer
✨Tip Number 1
Familiarise yourself with Relay's tech stack, especially GCP, BigQuery, and dbt. Understanding these tools will not only help you in interviews but also demonstrate your genuine interest in the role.
✨Tip Number 2
Engage with the logistics and data analytics community online. Join forums or LinkedIn groups where professionals discuss trends and challenges in the industry. This can provide insights that may be useful during your conversations with Relay.
✨Tip Number 3
Prepare to discuss real-world applications of your previous work. Be ready to share specific examples of how you've built and maintained data warehouses, as well as how you've collaborated with cross-functional teams.
✨Tip Number 4
Showcase your problem-solving skills by thinking through potential challenges Relay might face in scaling their data infrastructure. Presenting thoughtful solutions can set you apart from other candidates.
We think you need these skills to ace Senior Analytics Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in analytics engineering, particularly with SQL, BigQuery, and dbt. Emphasise any projects where you've built or maintained data warehouses, as this is crucial for the role.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for Relay's mission to reduce friction in e-commerce. Mention specific aspects of their tech stack that excite you, such as their use of Python and machine learning, and how your skills align with their needs.
Showcase Your Problem-Solving Skills: Provide examples in your application of how you've defined problems clearly and measured your impact in previous roles. This aligns with Relay's value of aiming with precision and will demonstrate your fit for their culture.
Highlight Collaboration Experience: Since the role involves working closely with engineers and business leaders, include examples of past collaborations. Discuss how you've gathered requirements from non-technical stakeholders and guided them in choosing the right data.
How to prepare for a job interview at Relay Technologies
✨Understand the Tech Stack
Familiarise yourself with Relay's tech stack, especially GCP, BigQuery, and Python. Be prepared to discuss how your experience aligns with their use of these technologies and how you can contribute to their data infrastructure.
✨Showcase Your Data Experience
Highlight your previous experience in building and maintaining data warehouses, particularly in fast-growing environments. Be ready to provide specific examples of how you've improved data processes or models in your past roles.
✨Communicate Effectively
Since you'll be working closely with both technical and non-technical stakeholders, practice explaining complex data concepts in simple terms. This will demonstrate your excellent communication skills and ability to collaborate across teams.
✨Prepare for Live Coding
Expect a SQL live coding session during the interview process. Brush up on your SQL skills, particularly in BigQuery and PostgreSQL, and practice writing queries that are efficient and scalable to showcase your technical prowess.
