About the role

The Data Engineering Manager will lead the data engineering team to deliver robust data pipelines and datasets while aligning with the company's Data & AI strategy. They are responsible for enforcing engineering standards, managing team capacity, and collaborating with cross-functional teams to support organizational data needs.

What they look for

Data Engineering Data Platform Snowflake Data Modeling Data Processing CI/CD Code Quality Testing Agile Scrum Kanban Jira Team Management Data Architecture Leadership Strategy

Requirements

Candidates must hold a higher education degree in Computer Science or a related field and possess at least 8 years of experience in data engineering or architecture. Proven experience in managing a data team and expertise in Snowflake environments and modern data platform development are required.

Full description

Data Engineering Manager

The success of a company depends on the passionate people we partner with.

Together, let's share our talents.

As a global leader in animal health, Ceva Animal Health believes our success is linked to our passionate people researching, developing , producing and supplying innovative health solutions for all animals, which contributes to the future of our diverse planet.

We are committed to ensuring the highest possible level of care and well-being for farm animals (poultry, pigs, ruminants), companion animals (dogs and cats) and wildlife.

Indeed, Our “Together, Beyond Animal Health” vision emphasizes that the health and wellbeing of people, animals and our planet are totally interlinked. More than ever, Ceva is committed to a "One Health" approach.

As part of our “Diversity, Equity and Inclusion” policy, Ceva Animal Heath is committed to the employment of people with disabilities and will make reasonable accommodations throughout the interview process to ensure an inclusive and accessible experience for all applicants. To request an accommodation, please contact a member of the Ceva Talent Acquisition team.

Your missions :

Context:

As part of the acceleration of our Data & AI strategy, we are looking for a Data Engineering Manager to lead and develop our Data Engineering team. You will be responsible for the delivery of pipelines and datasets, the application of engineering standards, and supporting teams in a context of Data Platform development and Data & AI transformation.

Main Responsibilities:

Vision & Strategy

- Translate the Data Platform roadmap into an operational delivery plan. - Contribute to the development of the Group’s Data Platform and its Data & AI transformation.

Design & Delivery

- Ensure the delivery of pipelines and datasets, while meeting quality standards and delivery timelines. - Allocate engineering resources and manage team capacity. - Oversee the implementation of Data solutions (pipelines, data modelling, data processing).

Governance, Quality & Compliance

- Enforce engineering standards (CI/CD, security, code quality, testing). - Ensure the robustness and scalability of pipelines.

Continuous Improvement & Innovation

- Optimise engineering processes and costs. - Implement development and industrialisation best practices.

Collaboration & Technical Leadership

- Ensure technical alignment with the Data Platform Architect. - Collaborate with Data, BI, AI and IT teams to support organisational needs.

Management

- Lead, support and develop a team of Data Engineers. - Drive team activities and foster an agile and efficient way of working (Scrum, Kanban, Jira).

Your profile :

Your Profile:

- Higher education degree in Computer Science, Data, or a related field. - At least 8 years of experience in Data Engineering, Data Platforms or Data Architecture. - Successful first experience managing a Data team. - Experience building, launching or bringing a modern Data Platform into production. - Strong understanding of Snowflake environments and Data Engineering topics (pipelines, data modelling, data processing). - Solid knowledge of engineering best practices (CI/CD, code quality, testing, industrialisation). - Experience leading teams in Agile environments (Scrum, Kanban, Jira). - Leadership, pragmatism and a strong delivery mindset. - Comfortable working in transformation and build-up environments. - Fluent English, both written and spoken.