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!
**What you will do**:
- Lead the development of efficient, scalable data pipelines using GCP tools.
- Co-define architecture alongside senior data engineering leaders.
- Build both batch and streaming pipelines, adapting to various business needs.
- Enable monitoring, logging, and validation across the pipeline lifecycle.
- Partner with analysts to ensure datasets are accessible and optimized for consumption.
- Improve code quality and reusability across data workflows.
- Support team members with reviews and technical coaching.




- Identify opportunities to streamline or modernize the platform.
- Ensure data reliability and consistency in daily and long-term delivery.
**What we are looking for**:
- Proficiency in BigQuery, SQL, Cloud Functions, Cloud Storage
- Experience coding and debugging, automation and testing
- Understanding of data design patterns and cloud-native architecture.
- Ability to build and troubleshoot robust and efficient pipelines.
- Quality
- and performance-driven mindset.
- Strong ownership mindset and structured approach to documentation and testing.
- Collaboration across tech and functional teams.
- Ownership and proactive problem-solving.
**Years of experience required**:
4-6 years in data engineering, with 2+ in a team or technical leadership capacity.
**Tools & Technologies**:
- BigQuery (advanced use)
- SQL, Python
- dbt, Dataform for transformation
- Airflow, Cloud Composer
- CI/CD pipelines and versioning tools (Git, GitLab, etc.)
- GCS, Pub/Sub, structured & semi-structured data formats (JSON, Parquet)
**Technical knowledge / certifications**:
- Strong in query optimization and storage design
- Experience implementing data validation and monitoring logic
- GCP familiarity mandatory, certification is a plus
Experience defining reusable transformation logic across domains

📌 Data Engineer (México)
🏢 L'Oréal
📍 México