About the Role We seek a highly skilled and motivated Sr Data Engineer with a strong focus on cloud-native data platforms and modern DevOps practices to join our dynamic team. As the Sr Data Engineer, you will be pivotal in shaping the technical direction of our data-centric products and features, leveraging the power of AWS cloud services and the Databricks unified data analytics platform. This is a position requiring deep technical expertise, a passion for data, and a proven ability to guide and mentor engineering teams in building scalable, reliable, and automated data solutions. You will be the subject matter expert for all data-related aspects of our product development lifecycle, ensuring operational excellence through DevOps principles. Experience in the commerce domain is a significant advantage. If you're excited by the challenge of building and optimizing high-impact data systems within a global beauty leader, we encourage you to apply.

Key Responsibilities:

• Technical Leadership: Providetechnical guidance to a team of data engineers, fostering best practices in AWS data services, Databricks development, and DevOps methodologies forthesuccessful delivery of high-quality, scalable data solutions.
• Architecture & Design: workinthe design and implementation of robust data architectures, pipelines, and systems that support our product strategy. This includes selectingappropriate AWSservices (e.g., S3,API Gateway, Lambda, DynamoDB, IAM, Kinesis,EC2), designingend-to-end pipelinesfor Databricks Lakehouse (Delta Lake), and ensuring data integrity and performance.
• Data Strategy: Collaborate with product management and business stakeholders to define and execute our data strategy, aligning technical solutions with businessobjectives, particularly through the strategic adoption of cloud and data platform capabilities.
• Code Quality & Performance: Champion best practices in code quality, testing, and performance optimization within Databricks notebooks/jobs and other data applications. Implement and advocate for CI/CD pipelines for data solutions, conduct thorough code reviews, and ensure the maintainability and scalability of our data infrastructure.
• DevOps & Automation: Drive the adoption of DevOps principles across the data engineering lifecycle, including infrastructure as code (IaC) using tools like CloudFormation or Terraform, automated testing, deployment automation for Databricks workloads, and robust monitoring and alerting for data pipelines and services on AWS.
• Innovation: Stay abreast of emerging technologies and features in the Cloudecosystem, Databricks platform, and general data/DevOps space. Explore innovative solutions to enhance our products and data capabilities, promoting a culture of continuous improvement.
• Collaboration: Work closely with cross-functional teams, including product management, data science (especially inan AIModels), and business intelligence, to deliver impactful data-driven solutions.
• Technical Roadmap: Contribute to the development and execution of the technical roadmap for our data products, aligning with overall business goals andleveragingstrategic cloud and data platform advancements.
• Mentorship & Development: Mentor and guide junior team members, fostering their technical growth and development in cloud data engineering, Databricks, and DevOps practices.
• Documentation: Create andmaintaincomprehensive technical documentation, including architecture diagrams for clouddata flows, design specifications for Databricks Lakehouse implementations, data dictionaries, and operational runbooks for automated pipelines and deployments. This documentation will be essential for knowledge sharing, onboarding new team members, and ensuring the long-term maintainability of our data systems.

Qualifications:

• Bachelor's orMaster's degree in Computer Science, Data Engineering, ora relatedfield.
• Proven experience as a Technical Lead or Principal Engineer, with a strong focus on data-intensive applications and cloud environments.
• Deep understanding of data warehousing, ETL/ELT processes, and data modeling techniques, particularly in a cloud-native context.
• Expertisein designing, building, and optimizing data solutions on AWS,utilizingservices such as S3, Lambda, Kinesis,EC2,DynamoDB,IAM, API Gateway, Step Functions, and DMS.
• Extensive hands-on experience with the Databricks platform, including Spark, Delta Lake, Databricks SQL,MLflow(AI Models), and workspace management.
• Proficiencyin SQL and at least one scripting language (e.g., Python,Java, Scala) for data engineering tasks.

Why L'Oréal? Join a company that puts innovation at the heart of its business, offers diverse career paths, and champions sustainability and ethical practices. You will have the opportunity to work on exciting projects that directly impact millions of consumers globally, leveraging cutting-edge technologies in a collaborative and supportive environment.

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.