Senior Data Engineer

Unleash Your Potential at L'Oréal's Beauty Tech!

Who Are We?

For 115 years, L’Oréal, the world's leading beauty player, has devoted itself to one thing only: fulfilling the beauty aspirations of consumers around the world.

For more than a century, L’Oréal has devoted itself solely to one business: Beauty. Present in 150 countries across five continents and with €42 billion in consolidated sales, L'Oréal is the global industry leader. With 37 global beauty brands across four divisions, L’Oréal offers beauty for all, covering every beauty category and catering to all beauty aspirations. With the acquisition of the Australian brand Aēsop in 2023, the Group continues to expand its portfolio through targeted acquisitions as part of its drive to create the future of beauty.

Today, L’Oréal includes more than 2,000 tech professionals and is constantly growing. Beauty Tech is changing the game and leading the shift toward new consumer realities and digital disruption. Championing Beauty Tech, we invent the beauty of the future while becoming the company of the future.

Beauty Tech is how we know our consumers intimately, augmenting their beauty journeys with unparalleled, diverse, and sustainable experiences. Beauty Tech equips the Group with the key assets it needs to conquer this new world, where technology has become strategic. With this ambition, L’Oréal continues to recruit diverse, innovative, skilled, and passionate minds across domains such as Data, Digital, Cloud, Cyber Security, IT Architecture, DevOps, Applications, and Infrastructure.

A Day in the Life of a Senior Data Engineer!

Main Responsibilities

A technical expert with leadership capabilities to guide the team, design robust architectures, and mentor engineers. Accountable for data engineering team efficiency, development sustainability, and risk management to deliver scalable and secure data solutions for the L'Oréal Beauty Tech Data Platform.

Required Skills

Advanced Technical Expertise (includes all Data Engineer skills, plus):

• System Architecture: Design and implement large\-scale, end\-to\-end data architectures on GCP.
• Performance Tuning: Expert optimization of complex pipelines and BigQuery for cost efficiency and scalability.
• Advanced Data Modeling: Slowly Changing Dimensions (SCD), Data Vault modeling, and complex data scenarios.
• Advanced Programming: Python for custom frameworks and complex processing logic.
• Infrastructure as Code: Terraform for cloud infrastructure management.
• Containers \& APIs: Docker, serverless architecture, API development, and API security (OWASP).
• Agile: Expert knowledge of Agile methodologies and ceremonies.

Leadership \& Mentoring

• Lead and manage technical teams (task delegation, code reviews, and constructive feedback).
• Mentor junior and mid\-level data engineers through cross\-learning and peer programming.
• Design and implement onboarding processes and ongoing training programs.
• Provide technical and methodological guidance and coordinate implementations.

Strategic \& Collaborative Skills

• Project Management: Translate business needs into technical specifications, estimate effort, and manage end\-to\-end projects.
• Stakeholder Communication: Excellent business and technical communication with analysts, BI developers, and business stakeholders.
• Governance: Establish and enforce data governance policies, quality standards, and engineering best practices.
• Risk Management: Identify and manage risks and proactively alert the team.
• Software Craftsmanship: Promote development best practices and identify and manage technical debt.
• Product Vision: Support the technical product vision, write technical user stories, and prioritize the technical backlog with Product Owners.

Cross\-functional Competencies

• Build collective intelligence and foster collaboration within the team.
• Manage the full application lifecycle.
• Environmental impact awareness (nice to have).

Certifications

Mandatory Certifications

• Google Cloud Certified \- Professional Data Engineer
• Google Cloud Certified \- Professional Cloud Architect

Nice to Have

• ITIL certification
• Security or DevOps certifications
• Terraform certification

Seniority

• Experience: 7\+ years in data engineering.
• Leadership: Minimum 2 years of experience leading projects, mentoring engineers, or making architectural decisions.
• Portfolio: Complex projects demonstrating expertise in scalable and reliable data solutions.
• Team Management: Demonstrated ability to ensure team efficiency and coordinate technical implementations.
• Technical Vision: Proven track record of supporting and implementing technical visions for data products.
• Production at Scale: Extensive experience deploying and maintaining data solutions in production environments.

What’s In It for You?

• Work with cutting\-edge technology, empowering employees with modern learning opportunities, global exposure, and future\-ready career paths.
• A flexible and modern workplace, enabling teams to perform at their best through a smart hybrid model that supports balance and autonomy, with a 3\-day in\-office, 2\-day work\-from\-home setup.
• Employee support at every life stage, with inclusive and progressive parental policies that help individuals and families thrive.
• Holistic wellbeing offerings, including personalized health benefits and strong mental wellness support to help employees feel their best.
• Reward and recognition opportunities, long\-term incentives, and the chance to share in L’Oréal’s collective success.

L'Oréal is an Equal Opportunity Employer and takes pride in fostering a diverse and inclusive environment.