Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineering Manager...

Royal Canin
London
16 hours ago
Create job alert

Job Description

Data Engineering Lead

The Platform & Engineering team at Royal Canin is responsible for managing our data capabilities, including 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 an experienced senior data engineer to join our team.

The Data Engineering Lead leads data engineering efforts for the team, with primary responsibility for delivering, managing and optimizing data pipelines, platforms, and workflows in the region. Reporting to the Head of Platform & Engineering, this role works on the global data platform to ensure data integrity, security, and high performance across both platforms to meet the business’s analytical and operational needs in APAC.

What are we looking for?

  • 5-10 years of experience in an Applied Data Engineering role or equivalent, ideally within the CPG, Consumer Products, Retail, Telecom or Financial Services industries.
  • Proficiency in SQL, Python, or other data-focused programming languages and data modeling principals.
  • Experience with big data technologies (e.g. Spark) and distributed data processing.
  • Good experience managing cloud-based data platforms, ideally Azure.
  • Experience developing using agile software development methodologies principles such as DevOps, CI/CD, unit testing.
  • Good understanding of Data Protection and Privacy principles and practices including GDRP.
  • Experience setting and monitoring the work of other technical resources, whilst retaining the engagement of a team of likeminded experts.
  • Ability to balance the needs of business and technical stakeholders.
  • Fluent in English

    What will be your key responsibilities?

  • Technical Leadership
  • Manage data engineering operations across the EU region on the global data platform, ensuring scalability, security, and reliability of assets and pipelines.
  • Lead a small team (2-4 FTE) of domain-specialized data engineers, providing them with the tools, guidance and support to perform their roles with excellence.
  • Ensure all product squads in D&A interface with your team for any global data asset requirements, ensuring proposed solutions are viable and utilize existing tools and processes.
  • Create and help execute a framework to break complex/functional requirements down into simple/technically manageable elements, with an understanding of the efforts required and any risks associated with development.
  • Co-ordinate, advise, and review both the problem-solving approach and code written by Data Engineers in your team, to increase quality of deliveries.
  • Engineering Innovation & Enhancement
  • Oversee evolution of platform technologies to improve quality, cost, and/or seek automation solutions to decrease overall effort. Work both with your team and broader stakeholders to implement such enhancements, whilst sharing with the RC Data Engineering community.
  • Provide an outside-in perspective, drawing innovations from the rest of Mars and industry into the RC data engineering community.
  • Work with the squad Product Manager and Scrum Master to increase engineering ways of working, leading to higher quality/faster delivery.
  • Help onboard any new development resources, ensuring they adopt coding standards set by the organization. Work with the Data Engineering community to evolve standards over time.
  • Data Management and Governance
  • Work with Data Domain Leads and Architects to ensure all data models and assets have Data Quality Management standards implemented, e.g. Metadata and Access Control, Data Lifecycle Management.
  • Partner with functions and divisions to ensure the RC data capabilities roadmap, operating model and governance principles are best serving the organization data strategy. Ensure compliance with relevant regulations and internal policies, such as GDPR, CCPA, or industry-specific standards.
  • Collaborate with Mars Petcare Data Engineering teams to generate synergies by sharing assets / best practice and mutualizing ways of working aligned with ecosystem strategy.
  • Data Engineering
  • Establish credibility with stakeholders at all levels of the organization. Act as an expert in complex or ambiguous business discussions, communicating Data Engineering related possibilities and concepts in a relatable way.
  • Partner with Product Managers and Data Domain Leads to ensure criteria for data quality, freshness and usability are understood and possible, so they can generate data-driven insights.
  • Monitor the operational performance of data systems and resolve escalated issues.
  • Assure your team are creating readable, manageable code, with proper monitoring, testing and CI/CD operations.
  • Ensure that product architecture and security is designed and implemented in accordance with RC & Mars standards, and in collaboration with architects.

    What can you expect from Mars?

  • Work with diverse and talented Associates, all guided by the Five Principles.
  • Join a purpose driven company, where we’re striving to build the world we want tomorrow, today.
  • Best-in-class learning and development support from day one, including access to our in-house Mars University.
  • An industry competitive salary and benefits package, including company bonus.

    #TBDDT

Related Jobs

View all jobs

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.