Analytics Engineering Manager

London
9 months ago
Applications closed

Related Jobs

View all jobs

Product Manager AI (AI & Machine Learning)

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Analytics Engineering Manager

London / Hybrid

Who We Are

Our ambition is to be the definitive food company, feeding people three times a day with great food from the World's best-loved restaurants, all with an unparalleled level of convenience.

From distributed computing to large-scale system design, complex algorithms to beautiful user interfaces, we have teams working on every step of the journey, in real-time, to ensure we continue to offer our customers a growing selection of choice at the best price with a fantastic level of service.

We work with thousands of restaurants worldwide, from renowned local gems to your favourite chains, allowing them to open up a new revenue stream and reach new customers. Our restaurant partners, riders and customers are as passionate about food as we are, and if you want to improve millions of users by solving some of the biggest technical challenges at great scale, come on board and join the ride.

The Team

Analytics Engineering is a growing area at Deliveroo. The team is a major enabler for Data science, Product Development and Business insight. Our analytics engineers are building our ETL, ingesting more and more data every day, building data models and data visualisations, all on our leading Cloud native data platform. Having demonstrated great impact, we need even more Analytics Engineers and more Analytics Engineering managers to support them!

You will spend time:

  • Hire and grow a diverse, accomplished group of analytics engineers, gaining fantastic exposure to scaling a tech team at a unique pace

  • Create a learning environment for your team while being a mentor for analytics engineers and up and coming leaders

  • Line managing one or more teams of analytics engineers

  • Work with other Analytics Engineering Managers to share understanding of multiple teams

  • Contribute to product delivery, by ensuring analytics engineers are in the right place at the right time

  • Become instrumental in improving and implementing processes and values that scale.

  • Provide technical mentorship to engineers building and deploying large-scale projects internationally

  • Collaborate with teams including product, design, operations

  • You will report to a Senior Data Science Manager and work closely with Directors & VP's of Engineering

    Requirements:

  • 3 years of experience as a Engineering Manager, managing individual contributors (Analytics Engineers/BI developers/Data Platform engineers)

  • Experience being an analytics/BI engineer at a mid/senior level, but is now not looking to do individual contributor work

  • Have worked with SQL in the last 2 years

  • Familiarity with modern cloud data stack (Snowflake, Prefect, Looker, or AWS)

  • Have experience working with senior partners in projects, and other team members business wide.

  • Experience working in a matrix organisation

  • Can bring together a group of individuals from many different backgrounds and skills to form a cohesive team.

  • Is comfortable managing ICs across multiple teams in different industries, and ruthlessly prioritising.

    This is a Hybrid position, requiring you to work from our London HQ 2-3 days per week

    Benefits

    At Deliveroo we know that people are the heart of the business and we prioritise their welfare. Benefits differ by country, but we offer many benefits in areas including healthcare, well-being, parental leave, pensions, and generous annual leave allowances, including time off to support a charitable cause of your choice. Benefits are country-specific, please ask your recruiter for more information.

    Workplace & Diversity

    At Deliveroo we know that people are the heart of the business and we prioritise their welfare. We offer multiple great benefits in areas including health, family, finance, community, convenience, growth and relocation.

    We believe a great workplace is one that represents the world we live in and how beautifully diverse it can be. That means we have no judgement when it comes to any one of the things that make you who you are - your gender, race, sexuality, religion or a secret aversion to coriander. All you need is a passion for (most) food and a desire to be part of one of the fastest growing start-ups around

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.