Global Data Engineer F/M/X

Mars, Incorporated
City of London
3 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Lead Data Engineer (GCP)

Lead Data Engineer (GCP)

Lead Data Engineer - Azure Synapse

Data Engineer

Job Description:


The Platform & Engineering team at Royal Canin is responsible for managing our data capabilities. This includes the creation, operation, and optimization of the data platform, assets, and pipelines. This is a growing team, supporting an advanced analytics agenda at Royal Canin that is rapidly transforming it into a business powered by data. To accelerate achieving this objective, we are looking for enthusiastic data engineers to join our team.


The role is responsible for creating and managing trusted and analytical Commercial and procurement data assets. You will be seen as the primary engineering contact for this area, with an expectation to provide expert advice and technical leadership for product squads utilizing data assets under your oversight; composed of product leaders, data scientists, data domain experts and front-end developers.


Key responsibilities:
Data Engineering

  • Engineer and orchestrate data flows & pipelines using high quality, easily deployable, repeatable and extensible codebases that ingest and integrate data from many disparate data sources in a cloud environment using a progressive tech stack.
  • Responsible for ensuring the quality, freshness and usability of supply chain in trusted zone(s).
  • Create readable manageable code with proper test and CI/CD, managing data transformation and troubleshooting data processing issues as required.
  • Follow RC Data Engineering best practices and contribute to their reinforcement, as well as shared assets such as Data Libraries.
  • Build simple data models to support efficient and accurate analytical insight creation. Reduce data preparation efforts for solution users to expedite their processes and reduce errors. Perform data pipeline migrations if necessary.
  • Implement alerting and monitoring capabilities to ensure high platform reliability in compliance with Mars Cyber Security Standards and Privacy Policies
  • Ensure that required expertise from outside the squad (e.g. architecture, cybersecurity) is engaged as appropriate.

Technical Leadership

  • Provide a technical viewpoint for product squads using data in your oversight, ensuring proposed solutions are viable and utilize existing tools and processes.
  • Seek to break complex/functional requirements down into simple/technically manageable elements, and with the help of others estimate the efforts required and any risks associated with development.
  • Partner with the Product Manager and Data Domain Lead to onboarding any new development resources, ensuring they adopt coding standards set by the organization.

Data Management and Governance

  • Practice Data Lifecycle Management through Global Metadata and Access Control Management.
  • Ensure all data models and assets have Data Quality Management standards implemented.
  • Partner with functions and divisions to ensure the RC data capabilities roadmap, operating model and governance principles are best serving the organization data strategy.


#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.

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.

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.

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.