Data Engineer

Royal Mail Group
London
2 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Royal Mail delivers more than our competitors put together. Yet we have ambitious plans to grow market share both at home and globally, whilst transforming our UK operation to increase efficiency and profit. Our strategy clearly sets out these plans – data and technology is pivotal to its success.

This Data Engineer position will play a pivotal role in driving Royal Mail's data strategy, collaborating closely with our Data Analytics and Data Science teams.

As a Data Engineer you will:

  1. Drive simple, standardised and innovative ways to ingest, process, store, analyse various data sources.
  2. Design, implement and monitor our cloud data platform (GCP).
  3. Work with the Data Science team to deploy machine learning user cases to production.
  4. Drive automation in the continuous integration pipelines, infrastructure management and configuration.
  5. Drive partnerships with engineering and product/business teams to deliver on cross-functional value and collaboration.
  6. Contribute to resource allocation, prioritisation, and delivery of data products, while collaborating with senior engineers and stakeholders.
  7. Own the technical lifecycle of data products, from design through delivery and support, ensuring alignment with customer outcomes and agile practices.
  8. Design and optimise scalable, cost-effective data solutions on GCP.

Key Skills & Experience:

  1. Experience in data engineering, delivering measurable value to organisations.
  2. Proficient in scripting languages (Python, Scala), with a plus in Big Data technologies (Spark, Kafka) and real-time data ingestion.
  3. Hands-on experience with Google Cloud tools (BigQuery, Dataflow, PubSub) or equivalent AWS/Azure tools.
  4. Good understanding of SQL, databases, ETL/ELT processes, data governance, and data visualization.
  5. Familiar with tools like JIRA, Confluence, CI/CD (Jenkins, Kubernetes), and testing methodologies (TDD/BDD).
  6. Experience with multi-cloud distributed applications, particularly on Google Cloud Platform and Azure.

What we offer you:

  • 18% Bonus
  • Car allowance (or cash alternative)
  • Hybrid Working (generally 3 days in office)
  • 25 days holiday (plus the option to buy more)
  • Plus, many more benefits!

Interview process and next steps:

We aim to move as quickly as possible! If your application is successful, you will be contacted by one of our recruitment team who will discuss the two-stage interview process with you.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

How to Write a Winning Cover Letter for Machine Learning Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for machine learning jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the machine learning sector. When applying for a machine learning job, your cover letter is a vital part of your application. Machine learning is an exciting and rapidly evolving field, and your cover letter offers the chance to demonstrate your technical expertise, passion for AI, and your ability to apply machine learning techniques to solve real-world problems. Writing a cover letter for machine learning roles may feel intimidating, but by following a clear structure, you can showcase your strengths effectively. Whether you're just entering the field, transitioning from another role, or looking to advance your career in machine learning, this article will guide you through a proven four-paragraph structure. We’ll provide practical tips and sample lines to help you create a compelling cover letter that catches the attention of hiring managers in the machine learning job market.

Jobs Careers

Veterans in Machine Learning: A Military‑to‑Civilian Pathway into AI Careers

Introduction Artificial intelligence is no longer relegated to sci‑fi films—it underpins battlefield decision‑support, fraud detection, and even supermarket logistics. The UK Government’s 2025 AI Sector Deal forecasts an additional £200 billion in GDP by 2030, with machine‑learning (ML) engineers cited as the nation’s second most in‑demand tech role (Tech Nation 2024). The Ministry of Defence’s Defence AI Strategy echoes that urgency, earmarking £1.6 billion for FY 2025–28 to embed ML into planning, logistics, and autonomous systems. If you have ever tuned a radar filter, plotted artillery trajectories, or sifted sensor data for actionable intel, you have already worked with statistical modelling—the backbone of machine learning. This guide shows UK veterans how to reframe military experience for ML roles, leverage MoD transition funding, and land high‑impact positions building the models shaping tomorrow’s defence and commercial landscapes. Quick Win: Bookmark our live board for Machine‑Learning Engineer roles to see who’s hiring today.

Jobs

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

🍪 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.