Data Engineer

London
3 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer | Hybrid Role | £50k-£60k | London

Route delivers world-class audience measurement for out-of-home advertising across Great Britain. We're building new data models and collection methods to better understand how people move and which OOH ads they see. You'll build the data pipelines and infrastructure that makes this happen.

Note: Applicants must be eligible to work in the UK, as visa sponsorship is not available.

Why this role?

From day one, you'll have the freedom to innovate and make decisions that directly affect the business. This isn't a traditional data engineering role; you'll wear multiple hats. You'll design and maintain local and cloud (GCP) data pipelines that power our analytics and dashboards and automate key processes. This includes managing our local infrastructure, including Proxmox virtualisation hosts and network configuration, ensuring seamless integration between on-premises and cloud systems. Working closely with the team, you'll get hands-on experience with everything from data engineering to infrastructure management.

What's in it for you?

Immediate Impact: Your work directly supports how audience data is used to measure advertising effectiveness across GB. You'll see results quickly, whether it's improving data quality, automating tasks, or building tools that surface insights.
Career Growth: You'll work with Python, Go, SQL, PostgreSQL, BigQuery, Google Cloud, and DevOps practices. With dedicated study days and a supportive team, you'll accelerate your learning and development.
Visibility: In a small team, your ideas matter. You'll have direct access to senior leadership and influence how data is used across the business.
Flexibility: Hybrid working (2-3 days in office) with flexible remote options.
Work-Life Balance: With 25 days holiday, private healthcare, and a social, relaxed working environment.
What you'll do:

Build and maintain data pipelines that are fast, reliable, and ready for analysis.
Manage local server and cloud infrastructure using DevOps practices, in a hybrid cloud environment.
Run quality checks and validation on release datasets. Automate routine checks, loading, and reporting.
Create dashboards that turn complex data into clear, actionable insights for internal teams and external stakeholders.
Support the insight team with data analysis and handle queries from industry stakeholders.
What we're looking for:

Experience building ETL pipelines, preferably with Python.
Strong SQL skills. Experience with PostgreSQL and BigQuery preferred.
Experience with cloud platforms, ideally Google Cloud.
Hands-on experience with Infrastructure-as-Code like Terraform.
Solid Linux/Unix skills, especially for server and network config.
Ability to communicate with both technical and non-technical people.
Ability to work independently with minimal supervision

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.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

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

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.