Data Engineer

Ziff Davis
London
9 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Description Position at RetailMeNot


With over 8 million members, VoucherCodes is one of the UK’s largest money-saving websites. Partnered with big brands like ASOS, Nike, Argos, Expedia, and Pizza Express, we receive over 8 million visits per month. We are currently seeking a Data Engineer to join our Engineering team in London. Our team designs, develops, and operates all data systems across the company, including ETL processes, data warehouses, real-time click streams, and EMR to support content personalization for our users.


We are looking for someone to help us evolve our data architecture and technology stack. Our primary programming language is Python, although some systems still run in PHP and are being migrated to Python. We manage our own AWS account and Kubernetes cluster with EKS. Our collaboration with the Platform Team ensures adherence to best practices and standards, maintaining our infrastructure independently.


The ideal candidate will have strong software development experience with Python and SQL, along with a keen interest in working with Docker, Kubernetes, Airflow, and AWS data technologies such as Athena, Redshift, and EMR. You will join a team of over 25 engineers across mobile, web, data, and platform domains, and should demonstrate excellent attention to detail and a commitment to quality.


What we need from you:


  • At least 3 years of relevant data engineering experience
  • Strong Python and SQL skills
  • Experience with dbt
  • Experience with AWS
  • Experience working with a columnar database such as Redshift
  • Extensive experience with ETL/ELT and managing data pipelines
  • Familiarity with Snowplow
  • Experience integrating data from various sources
  • Good cross-team communication skills
  • Familiarity with CI/CD practices and tools
  • Understanding of Agile Scrum development lifecycle


What you’ll be doing:


  • Implementing and maintaining ETL pipelines using Airflow and AWS technologies
  • Contributing to data-driven tools, including content personalization
  • Managing ingestion frameworks and processes
  • Monitoring and maintaining our data infrastructure in AWS
  • Supporting Business Analytics and Marketing teams


What you’ll get from us:


  • A culture that encourages you to be your best
  • Two hours weekly dedicated to personal development
  • A personalized development plan for career growth
  • Flexible work arrangements for work/life balance
  • Recreational activities like Zumba, football, table football, and pool
  • Quarterly team socials


Working Pattern

Hybrid, with a minimum of 1-2 days per week in our London office (Yeoman House, Sekforde Street, London, EC1R 0HF). Our office is in the vibrant Clerkenwell area, surrounded by cafés, restaurants, pubs, and galleries, with excellent street food options nearby. We offer flexibility for remote work to support work/life balance.


Next Steps

If interested, please send your CV along with a 200-300 word cover letter explaining why this role and VoucherCodes appeal to you. Use this space to share what excites you about this opportunity.


VoucherCodes is part of Ziff Davis, a digital media and internet company (Nasdaq: ZD) with a portfolio spanning technology, entertainment, shopping, health, cybersecurity, and martech. We aim to build a sustainable, profitable, and growing enterprise, emphasizing the importance of talented people, technology, and culture.


For more information, visit our careers page.


#J-18808-Ljbffr

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.

Jobs

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

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.

🍪 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.