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.
Data Engineering Manager, Analytics Products leads and develops a team of data engineers 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, analytics products.
* 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 ambugity 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 solution 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 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 and other local and goevernance regulations applied to CPG and retail industries.
* Ability to create a technical community with both internal and external engioneers 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-fucnctional 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 perespective on DevOps practices and support models