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:

At L'Oréal, Data Engineers are crucial for empowering data-driven decisions by ensuring data is accessible, reliable, and analysis-ready. As a key member of our team, the ideal candidate will build and maintain the data infrastructure that powers our data pipelines and machine learning initiatives. This role demands expertise in designing and implementing data pipelines, ensuring data quality, and enabling seamless integration with ML models. The ideal candidate possesses a solid understanding of GCP’s data services and a passion for building scalable and efficient data solutions.

• Design and develop robust and scalable data pipelines using GCP services like Dataflow, Cloud Composer, Cloud Functions, Cloud Run, Big Query and Pub/Sub ensuring data quality, performance, and scalability.
• Develop and optimize Extract, Transform, Load (ETL) processes using GCP tools like Dataflow, Dataproc, and Cloud Functions.
• Create robust and automated pipelines in GCP to ingest and process structured and unstructured data from source systems into analytical platforms using batch and streaming mechanisms leveraging cloud native toolset.
• Design and implement efficient data models for analytical and reporting purposes, considering data governance and best practices.
• Collaborate with data scientists to design and implement feature engineering pipelines using GCP tools such as BigQuery ML and Dataflow.
• Create and deploy innovative solutions based on Machine Learning, Deep Learning or Generative AI for a variety of retail use cases.
• Collaborate with data architects, ETL developers, engineers, BI developers/data scientists, and information designers to identify and define required data structures, formats, pipelines, metadata, and workload orchestration capabilities.
• Implement data quality checks, validation rules, and data lineage tracking to ensure data accuracy and compliance.
• Manage and optimize GCP resources related to data processing, storage, and analysis, including cost optimization.
• Monitor data pipeline performance and identify and resolve bottlenecks, and troubleshoot data-related issues.
• Automate data processing tasks and workflows using scripting languages like Python and shell scripting.

• Provide thought leadership and new perspectives on data science projects and how to leverage GCP cloud services and capabilities.

What we are looking for: 

• 6+ years of overall experience in data analytics through data architecture, data engineering, machine learning or deep learning systems.
• Experience designing, building, and maintaining robust and scalable data pipelines using GCP tools, including ETL processes, data ingestion, transformation, and loading.
• 3+ years of experience in providing technical leadership from design to implementation of creative data solutions involving GCP services (Big Query, DataFlow, Cloud Functions, Cloud Run, GCS pub/sub, Composer, Vertex AI).
• Strong SQL skills for data manipulation and querying. High proficiency in Python for data processing and pipeline orchestration.
• Understanding of data warehousing concepts, dimensional modelling, and schema design.
• Experience working with recommendation engines, data pipelines, or distributed machine learning.
• Comfort with data science ecosystem such as pandas, numpy, pytorch, etc.

• Experience with development tools such as GIT, Docker, Terraform and MLOps 

• Knowledge of data governance principles and best practices. Experience implementing data quality checks and validation rules.
• Familiarity with BI platforms such as Power BI
• GCP Data Engineering or Cloud Architect Certification
• Full stack development experience a plus

Business Intelligence and Domain Expertise:

• Experience working with business stakeholders to gather requirements and translate them into clear technical specifications for BI solutions.
• Experience working with business analysts to identify the necessary data sources and ensure data quality for reporting and analysis.
• Contributing to the development of BI strategies and roadmaps within the organization and helping to shape the direction of BI development

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.