Data Engineer - DataOps

Job Description

Do you have a Data Engineer profile with database experience and a passion for process automation? Join a transformative project that is revolutionising the olfactory experience industry!

We are looking for a mid to senior level Data Operations Engineer, with the possibility to evolve into a Data Governance expert role with ownership of the company's data area.

About the project: You will be key in the development and optimisation of the data infrastructure, helping to ensure the quality of the data that drives their strategic decisions and improves their personalised recommendations. You will collaborate closely with marketing, business development and perfumery teams, ensuring a clean and reliable data flow, while executing automations and continuous improvements to their databases.


Responsibilities:

• Automate data processes: Implement solutions that ensure data integrity and accessibility in real time.
• Mapping and optimising databases: Ensure an efficient and scalable structure, managing enhancement requests that align with business needs.
• Data quality implementation: Monitor and maintain high standards of data quality, identifying opportunities for continuous improvement.
• Web scraping and AI: Execute scraping tasks to keep the database complete, and leverage artificial intelligence through APIs to enrich data analysis.
• Prepare for a pivot to Data Governance: Create a solid foundation of data practices that will enable a transition to a comprehensive data governance approach at the end of the initial project.

Benefits:

• Attractive remuneration package
• To be part of an innovation project within a large multinational company.
• Good collaborative and international working environment
• Ad-hoc training plan
• Ambitious career plan

If you are ready to take on a strategic role and are motivated to build a high-impact data infrastructure, we invite you to join us and make every piece of data count!

Professional Requirements

• Experience in Data Engineering and database administration, with 3-5 years for mid-level candidates and 5+ years for senior candidates.
• Proficiency in SQL, automation and Data Engineering best practices.
• Knowledge of web scraping tools and AI integration to improve data functionality.
• Excellent communication skills to collaborate with technical and non-technical teams, and a focus on continuous improvement.