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Senior Analytics Engineer
Исключительная вакансия в одном из самых успешных стартапов Европы с огромным пакетом опционов и сильной инженерной культурой. Работа над передовыми AI-решениями в логистике делает эту роль профессионально привлекательной.
Сложность вакансии
Высокая сложность обусловлена требованиями к глубокому техническому стеку (dbt, BigQuery, Python) и необходимостью работать в высоконагруженной среде с AI-агентами. Ожидается опыт более 5 лет и способность проектировать сложные архитектуры данных с нуля.
Анализ зарплаты
Зарплата не указана, но компания заявляет о 'щедром капитале' (equity), превышающем 99% европейских стартапов. Рыночные оценки для Senior Analytics Engineer в Лондоне в топовых стартапах обычно начинаются от £80,000-£100,000 плюс значительный пакет акций.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Analytics Engineer position at Relay. With over five years of experience in data modeling and a deep proficiency in SQL, dbt, and Python, I have a proven track record of building scalable data architectures that drive both operational efficiency and strategic decision-making. My background in developing complex DAGs and partnering with cross-functional teams aligns perfectly with the needs of your Last Mile squad.
What excites me most about Relay is your mission to eliminate friction in commerce and your commitment to first-principles thinking. I am particularly drawn to the opportunity to build the foundations for your agentic AI workflows and to contribute to a marketplace that is scaling at an unprecedented rate. I am eager to bring my expertise in BigQuery and real-time data pipelines to help Relay continue its trajectory as a leader in the logistics industry.
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Откликнитесь в relay уже сейчас
Присоединяйтесь к Relay, чтобы строить будущее логистики с использованием ИИ и получить долю в одной из самых быстрорастущих компаний Европы!
Описание вакансии
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
Relay’s Mission is 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.
THE TEAM• ~110 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
The Opportunity
At Relay, we rely on data to guide how every parcel moves through our network — from when it enters the system to when it's delivered at the doorstep. Our data infrastructure is the backbone that powers everything from real-time operational decisions to strategic business insights to networks of autonomous AI agents.
We're looking for a Senior Analytics Engineer to sit within our Last Mile squad; our biggest and most data rich squad. Your role will help contribute to the success of the key agentic workflows that power our Last Mile marketplace.
You'll be joining at an exciting moment as we grow rapidly and expand our network across the UK.
Who Will Thrive in this role?
- Design core data models - Partner with engineers and business leaders within the Last Mile squad to design and build foundational data models that power analytics, data science and AI workflows
- Build the foundations for our key AI systems - Our Last Mile marketplace is becoming increasingly agentic, you will be a key owner of the inputs that power these systems
- Drive data quality - Implement testing, monitoring, and alerting to ensure our data is accurate, timely, and trustworthy
- Collaborate - Work with team members across the business to understand their data needs and deliver solutions
- Shape our practices — Help define and evolve our analytics engineering processes and standards as we scale
What We're Looking For
- 5+ years of experience as an analytics engineer, data engineer, data analyst or similar role
- Extensive experience with SQL, particularly with BigQuery and PostgreSQL
- Demonstrated experience with dbt, with a track record of building and maintaining efficient, scalable, and reliable DAGs
- Python proficiency for data manipulation, scripting, and automation
- Experience with data visualisation tools such as Tableau, Looker, or similar
- Experience in effective communication, particularly in gathering requirements and guiding non-technical stakeholders to the right data solutions
- Familiarity with using AI tools to accelerate your workflow
Nice to Have:
- Experience with orchestration tools like Dagster, Airflow, or similar
- Experience building real-time or near-real-time data pipelines
- Familiarity with machine learning workflows and feature engineering
- Experience embedded in teams building customer facing products
- Previous experience of learning and modelling an unfamiliar operational domain
- A desire to see the real world impact of what you work on!
Compensation, Benefits & Workplace
- 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).
- Located in Shoreditch, our office set-up enables the kind of in-person interactions that drive impact. We work 4 days on-site, with 1 day remote.
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.
If these resonate, and you combine strong technical fundamentals with entrepreneurial drive, let’s connect.
Relay is an equal-opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.
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Навыки
- Tableau
- Python
- Machine Learning
- SQL
- Looker
- dbt
- PostgreSQL
- BigQuery
- Airflow
- Data Modeling
- Dagster
Возможные вопросы на собеседовании
Проверка опыта работы с основным инструментом трансформации данных и понимания архитектуры.
Расскажите о самом сложном DAG, который вы проектировали в dbt: как вы обеспечили его масштабируемость и надежность?
Позиция предполагает работу с AI-агентами, поэтому важно понимать, как данные готовятся для моделей.
Как бы вы спроектировали слой данных для поддержки real-time AI-агентов в логистическом маркетплейсе?
Relay ценит качество данных и мониторинг.
Какую стратегию тестирования и алертинга данных вы бы внедрили для критически важных операционных метрик?
Проверка навыков оптимизации запросов в BigQuery.
С какими проблемами производительности в BigQuery вы сталкивались и как оптимизировали затраты и скорость выполнения запросов?
Оценка способности переводить бизнес-задачи на язык данных.
Опишите случай, когда вам пришлось убеждать нетехнических стейкхолдеров в необходимости изменения структуры данных или метрик.
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