Data Engineer

Royal Canin SA; Greater London; On-site; GBP 55,000 - GBP 75,000; Full time

Job summary

A global leader in pet nutrition is seeking a Data Engineer to join their dynamic Platform & Engineering team. This role focuses on creating and managing trusted commercial and procurement data assets, ensuring data quality and usability. You will lead data flows and support product development with technical expertise, while implementing best practices in governance and data management. The ideal candidate thrives in a cloud environment and is passionate about data-driven solutions.

Qualifications

• Strong experience in engineering and orchestrating data flows and pipelines.
• Ability to manage data transformation and troubleshooting data processing issues.
• Understanding of data lifecycle management and governance principles.

Responsibilities

• Engineer and orchestrate data flows & pipelines using high quality codebases.
• Provide technical guidance for product squads utilizing data.
• Implement data quality management standards.

Skills

Data engineering

Data flow orchestration

Cloud environments

CI/CD practices

Data models creation

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 onboard 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.