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- Tasks: Lead a team of data engineers to create and optimise data solutions.
- Company: Join Royal Canin, a purpose-driven company transforming into a data-driven organisation.
- Benefits: Competitive salary, bonus, and access to Mars University for continuous learning.
- Other info: Foster a vibrant engineering community and enjoy excellent career growth opportunities.
- Why this job: Make a real impact by driving engineering excellence in a collaborative environment.
- Qualifications: 8+ years in engineering management, strong product mindset, and proficiency in SQL and Python.
The predicted salary is between 80000 - 100000 £ per year.
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 data driven organisation.
To accelerate achieving this objective, we are looking for an experienced Data Engineering Manager with knowledge on Product Engineering to join our team. Senior Data Engineering Manager, Analytics Products leads and develops a team of data engineers (blend of associates and external 3rd party vendors) embedded across multiple cross-functional squads who work day-to-day with product, analytics, and business teams. Reporting to the Head of Platform & Engineering, this role is a critical link between the global data platform and the analytics squads, ensuring the speed and quality of delivery meets the business’s analytical needs.
The primary focus of this role is people leadership, engineering excellence, and community standardization, ensuring consistency, quality, and scalability across all analytical products. This role will not own a single product area but instead enable multiple squads to deliver high-quality data solutions through shared standards, best practices, and design thinking.
What are we looking for?
- An experienced engineering leader with a strong product mindset and technical background in building robust, analytical products (or analytical components within a B2B solution) by partnering with data science team and product managers.
- A leader who excels at coaching, mentoring, and developing data and software engineering talent with familiarity in managing engineers embedded in cross-functional teams or a matrix organization.
- Someone who is comfortable with ambiguity and thrives in a collaborative environment, partnering closely with product and analytics leaders to bring a vision to life.
- A strategic thinker who can guide technical decisions on architecture, weigh trade-offs, and ensure the team is building scalable and reliable solutions while delivering at speed.
- More than 8 years of experience in engineering and engineering management roles or equivalent, ideally within the CPG, Consumer Products, Retail, Telecom industries or Analytical B2B solution providers.
- Proficiency in SQL, Python, or other data-focused programming languages and data modeling principles.
- 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 GDPR and other local governance regulations applied to CPG and retail industries.
- Ability to create a technical community with both internal and external engineers and 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?
- People Leadership & Chapter Management: Manage, coach, and develop a distributed team of data engineers working across different squads. Conduct regular 1:1s, performance reviews, and career development planning. Foster a strong data engineering community with shared ownership and identity. Support hiring, onboarding, and retention of top engineering talent.
- Engineering Standards & Community Enablement: Define, implement, and enforce engineering standards across squads (coding, testing, documentation, data modeling). Establish best practices for pipelines, orchestration, and data reliability. Lead community rituals (team meetings, knowledge sharing sessions, design reviews). Promote reuse of data models, pipelines, libraries and tooling to avoid duplication.
- Engineering Architecture & Governance: Provide architectural guidance to engineers across squads. Ensure alignment and compliance with data platform usage (warehousing, orchestration, transformation ways of working). Drive consistency in data modeling approaches and semantic layers for analytics products. Champion data quality, observability, and governance practices.
- Cross-Squad Alignment & Delivery Enablement: Partner with product managers and tech leads to align on priorities and technical direction. Identify and enable cross-functional opportunities and dependencies across squads. Remove blockers and improve engineering productivity at scale. Balance autonomy of squads with the need for standardization.
- Operational Excellence: Improve development workflows, CI/CD practices, and deployment standards in collaboration with the platform team. Define and track engineering metrics (e.g., pipeline reliability, delivery velocity, data quality SLAs) in collaboration with platform team. Ensure incident management are defined and post-mortem practices are consistently applied. Lead engineering perspective on DevOps practices and support models.
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.
Data Engineering Lead employer: Royal Canin SAS
Contact Detail:
Royal Canin SAS Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineering Lead
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work at Royal Canin or similar companies. A friendly chat can sometimes lead to insider info about job openings or even a referral.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your projects, especially those involving SQL, Python, or big data technologies. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Ace the interview by being ready to discuss your leadership style and how you've developed teams in the past. Share specific examples of how you've fostered collaboration and innovation in cross-functional settings.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining the team at Royal Canin.
We think you need these skills to ace Data Engineering Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your leadership experience and technical expertise in data engineering, as these are key for the Data Engineering Lead role.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've led teams and delivered high-quality data solutions, and don't forget to mention your familiarity with big data technologies!
Showcase Your Technical Skills: Since this role requires proficiency in SQL, Python, and big data technologies, make sure to include relevant projects or experiences that demonstrate your technical capabilities. We want to see how you can contribute to our data-driven agenda!
Apply Through Our Website: We encourage you to apply directly through our website. This way, your application will be processed more efficiently, and you'll have a better chance of standing out to our hiring team!
How to prepare for a job interview at Royal Canin SAS
✨Know Your Data Engineering Fundamentals
Make sure you brush up on your SQL, Python, and big data technologies like Spark. Be ready to discuss how you've applied these skills in previous roles, especially in building analytical products or components. This will show that you have the technical chops to lead a team effectively.
✨Showcase Your Leadership Style
Prepare examples of how you've coached and developed engineering talent in the past. Think about specific instances where you fostered a strong community among your team members. Highlight your experience with performance reviews and career development planning to demonstrate your commitment to people leadership.
✨Understand the Business Needs
Be prepared to discuss how you balance technical decisions with business objectives. Think about times when you've partnered with product managers or analytics leaders to align on priorities. This will show that you can bridge the gap between technical and business stakeholders effectively.
✨Emphasise Your Agile Experience
Since the role involves working with agile methodologies, be ready to talk about your experience with CI/CD, DevOps practices, and how you've improved development workflows. Share specific metrics or outcomes that demonstrate your impact on engineering productivity and operational excellence.