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Permanent

Mexico City

Estado de México

Tech

Full

• Time

02-Feb-2026

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!

1. About the Role: Impact and Expectations

As a Data Engineer, you are at the heart of L’Oréal’s digital transformation. Your mission is to design, build, and optimize the robust data ecosystem that empowers our business sectors to make smart data-driven decisions

You will be expected to:

• Bridge Technology and Business: Transform complex business requirements into scalable technical architectures that deliver real-world value.
• Drive Innovation: Champion a cloud-native mindset, ensuring our data platforms are modern, efficient, and future-proof.
• Ensure Excellence: Act as a guardian of data integrity, ensuring that our analysts and stakeholders have access to high-quality, reliable, and "ready-for-consumption" datasets.
• Lead by Example: Contribute to a culture of technical excellence, mentoring peers and fostering a collaborative environment where we learn and grow together.

Key Responsibilities: What You Will Do

In this role, you will take full ownership of the data lifecycle, from ingestion to optimization. Your main objectives include:

• Scalable Pipeline Engineering: Lead the development of end-to-end data pipelines (both batch and streaming) using the full suite of GCP tools to support diverse business needs.
• Architectural Co-design: Partner with senior leadership to define and refine data architectures that are resilient, performant, and cost-effective.
• Infrastructure as Code (IaC): Use Terraform to provision and manage our cloud infrastructure, including Big Query datasets, Cloud Storage, and Dataflow jobs.
• DevOps & CI/CD Mastery: Implement and automate CI/CD pipelines for ETL scripts and Spark jobs, integrating automated testing and quality gates directly into the workflow.
• Quality Assurance & Testing: Apply rigorous testing best practices (Unit, Integration, E2E) and manage schema evolution to ensure zero-breakage deployments.
• Data Observability: Enable comprehensive monitoring and logging across the pipeline lifecycle to proactively identify and resolve issues.
• Stakeholder Partnership: Collaborate closely with Data Analysts to optimize datasets for consumption, ensuring they are structured for high-performance querying.

What We Are Looking For

We are seeking a proactive problem-solver with a passion for clean code and a "strong ownership" mindset.

Education & Experience:

• Proven Track Record: 4–6 years of experience in Data Engineering.
• Leadership Core: At least 2+ years in a team lead or technical leadership capacity, showing an ability to coach and mentor others.
• Education: A degree in Computer Science, Engineering, or a related technical field is preferred.

Technical Knowledge:

• GCP Ecosystem: Proficiency in Google Cloud Platform is mandatory. This includes Big Query (advanced level), Cloud Functions, Cloud Storage, and Cloud Composer. GCP certifications are a significant plus.
• Terraform Expertise: Deep experience in writing Terraform configurations to manage cloud resources is a core requirement.
• The Modern Data Stack: Strong hands-on experience with Python, SQL, dbt, and Dataform for advanced transformations.
• Orchestration & Versioning: Expertise in Airflow and version control tools like Git/GitLab.
• Data Design: A deep understanding of cloud-native architecture, data design patterns, and structured/semi-structured formats (JSON, Parquet).

Skills & Competencies:

• Performance Driven: A mindset focused on query optimization, storage design, and performance tuning.
• Collaborative Spirit: Excellent communication skills to work effectively across both technical and functional business teams.
• Structured Thinking: A methodical approach to documentation, testing, and troubleshooting.
• Agility: The ability to adapt to a fast-paced environment where technologies and business needs evolve rapidly.

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.

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