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Permanent

Mexico City

Estado de México

Tech

Full

• Time

09-Dec-2025

For more than a century, L’Oréal has devoted its energy, innovation, and scientific excellence solely to one business: Beauty. Our goal is to offer every person around the world the best of beauty in terms of quality, efficacy, safety, sincerity and responsibility to satisfy all beauty needs and desires in their infinite diversity.

At L'Oréal, our IT teams design and build solutions to ensure high performance for all our business sectors by imagining new ways of doing things, from designing websites to building algorithms and predicting new trends. They can be found leading teams towards a more connected and digitalized future in IT retail, e-commerce, CRM, data, AI, cybersecurity, Cloud and E-Marketing. You never stop learning at L'Oréal IT because things change at the speed of light! Come join our dynamic team!

About the Role:

We're seeking a highly experienced and forward-thinking Data Engineering Tech Lead to spearhead our Americas analytics workstream on Google Cloud Platform (GCP). This role demands deep expertise in data warehousing, ETL, data modeling, advanced analytics, API design and implementation in agile mode. A strong preference for domain (Commerce, Supply Chain etc.) specific data knowledge and a passion for building reusable and sustainable technical designs is essential. Proficiency with Google Cloud services in general and Data Engineering services in particular is crucial.

In this role you will be reporting to Americas Data Domain & Analytics Lead. You will be working closely with other Domains and Analytics specific Product Delivery Managers, Product Owners, Operations, Security, Architecture and Data Privacy teams

Responsibilities:

• Data Analytics Ownership: Own the Data Analytics roadmap and strategy within GCP, championing reusability and sustainability. Drive the development of data solutions tailored for your analytics workstream, such as commerce and supply chain reporting.
• Technical Leadership & Mentorship: Lead and mentor data engineers, fostering a culture of reusability, maintainability, and long-term sustainability. Provide technical guidance, code reviews, and career development support.
• Reusable & Sustainable Data Processing Pipelines: Evolve our data architecture, focusing on reusable components and frameworks for data processing, exposed through well-defined APIs. Design and implement scalable data pipelines using GCP services (Big Query, Cloud Dataflow, Cloud Functions, Cloud Composer, Cloud Run, Workflows) with modularity and reusability as core principles, leveraging APIs for inter-service communication.
• Modular Data Modeling & Warehousing: Develop and maintain robust data models in Big Query for domain analytics, prioritizing modular design for reusability. Optimize data structures for performance, scalability, and cost-effectiveness, ensuring long-term maintainability and adaptability. Develop solutions that traverse through the Medallion Architecture.
• Cloud Run & Containerization for Reusable APIs: Leverage Cloud Run for deploying and managing containerized API services. Design reusable container images and deployment patterns. Implement efficient CI/CD pipelines for Cloud Run deployments, integrating seamlessly with other GCP services.
• Big Query Optimization: Continuously optimize Big Query performance for domain analytics, focusing on long-term sustainability and cost efficiency. Design and implement APIs for controlled and efficient access to Big Query data including versioning, authentication, and authorization.
• Python Development for Reusable API Libraries: Utilize Python for building reusable API libraries and frameworks for data manipulation, analysis, and access. Streamline data engineering workflows through reusable code components and well-documented APIs.
• Collaboration & Communication: Collaborate closely with stakeholders to understand their data needs and deliver sustainable Data Engineering solutions. Communicate technical concepts effectively, emphasizing the value of tech solutions for data accessibility and integration.
• Innovation & Research for Data Solutions: Stay at the forefront of data engineering and google cloud development trends, exploring new approaches to enhance reusability, sustainability, and scalability of data solutions.

Qualifications:

• Bachelor’s degree in computer science, Engineering, or a related field.
• 10+ years of experience in data engineering, data warehousing and analytics.
• 4+ years of experience with Google Cloud Platform (GCP), including Big Query, Cloud Dataflow, Cloud Functions, Cloud Composer, Pub/Sub, Cloud Workflows, Cloud Build and Cloud Run.
• Proven experience in implementing Big Query Access Controls like Row and Column Level Security
• Experience implementing Data Governance and Data Quality standards
• Experience in GCP and PowerBI performance tuning and cost optimizations
• Proven experience in data warehousing, ETL processes, and data modeling.
• Experience with containerization technologies (Docker, Kubernetes).
• Experience with Terraform and DevOps tool chain.
• Solid proficiency in SQL and Python.
• Excellent communication, interpersonal, and teamwork skills.
• Strong problem-solving, analytical skills and self-driven attitude.
• Experience leading and mentoring a team of engineers.
• Google Cloud Professional Data Engineer Certification.
• Familiarity with Data Visualization Tools like PowerBI, Tableau.

Preferred Qualifications:

• Strong understanding of software design principles and patterns for building maintainable and scalable systems.
• Experience working with large-scale domain specific datasets and understanding of data structures and business processes.
• Understanding and exposure to AI and ML concepts and value addition from Data Engineering and software SDLC standpoint.

Don’t meet every single requirement? At L'Oréal, we are dedicated to building a diverse, inclusive, and innovative workplace. If you’re excited about this role but your past experience doesn’t align perfectly with the qualifications listed in the job description, we encourage you to apply anyways! You may just be the right candidate for this or other roles!

We are an Equal Opportunity Employer and take pride in a diverse environment. We would love to find out more about you as a candidate and do not discriminate in recruitment, hiring, training, promotion, or other employment practices for reasons of race, color, religion, gender, sexual orientation, national origin, age, marital or veteran status, medical condition or disability, or any other legally protected status.

• Position based in Mexico

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