Job Description:
The Platform \& Engineering team at Royal Canin is responsible for managing our data capabilities. This includes the creation, operation, and optimisation 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 Supply 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 utilising data assets under your oversight, composed of product leaders, data scientists, data domain experts and front-end developers.
What are we looking for?
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3-7 years of experience in an Applied Data Engineering role or equivalent, ideally within the CPG, Consumer Products, Retail, Telecom or Financial Services industries.
Applied knowledge of supply chain and associated data, e.g. procurement, manufacturing, logistics
Good experience in working with data (Python/PySpark/Databricks) in a cloud-based data systems environment (ideally Azure).
Experience in developing using agile software development methodologies, principles such as DevOps, CI/CD, and unit testing.
Comfortable working both by themselves and in a team setting. Strong planning and prioritisation skills.
Good understanding of Data Protection and Privacy principles and practices, including GDPR.
Great at developing new relationships, driving positive change, and matching analytics opportunities to data acquisition strategy.
Quick learner, with flexibility and willingness to adapt to new software and techniques.
Ability to communicate with business and technical stakeholders.
What will be your key responsibilities?
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Data Engineering
Engineer and orchestrate data flows \& pipelines using high-quality, easily deployable, repeatable and extensible codebases that ingest and integrate supply chain 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 data in trusted zone(s).
Create readable, manageable code with proper testing 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 product architecture and security are designed and implemented in accordance with RC \& Mars standards, in collaboration with architects.
Technical Leadership
Provide a technical viewpoint for product squads using data in your oversight, ensuring proposed solutions are viable and utilise existing tools and processes.
Break complex/functional requirements down into simple/technically manageable elements with an understanding of 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 organisation. Work with the Data Engineering community to evolve standards over time.
Coordinate and review work done by other Data Engineers in a squad to increase the quality of deliveries.
Engineering Innovation \& Enhancement
Oversee the evolution of platform technologies to improve quality/cost, or seek automation solutions to decrease overall effort. Manage any proposed enhancement through implementation, as well as sharing it with the Data Engineering community.
Work with the squad Product Manager and Scrum Master to increase engineering ways of working, leading to higher quality/faster delivery.
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. Design all new data models in collaboration with Data Domain Leads and Architects.
Partner with functions and divisions to ensure the RC data capabilities roadmap, operating model and governance principles are best serving the organisation's data strategy.
Collaborate with Mars Petcare Data Engineering teams to generate synergies by sharing assets / best practices and mutualising ways of working aligned with ecosystem strategy
What can you expect from Mars?
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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 a company bonus.
#TBDDT