Job description

Job Title Cloud Data Engineering & AI Tech Lead Division: Corporate IT, Data & AI Location: New York, NY Reports To: Data & AI – Domain Analytics Lead Who We Are: 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 each and 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: L’Oréal is driving a massive Beauty Tech Transformation roadmap, designing and implementing next-generation Data Products to accelerate business growth across Commerce and Supply Chain. As a Tech lead , you will design, build, and optimize scalable, secure, and reusable data products on Google Cloud Platform. You will combine strong hands-on data engineering expertise with practical AI engineering experience to make governed enterprise data available for analytics, reporting, and natural-language insight experiences. You will work closely with Data Architects, BI Developers, Data Scientists, Product teams, and business stakeholders to build reliable data foundations, standardize metric definitions, and enable trusted data access. This role requires strong technical ownership, a hands-on delivery mindset, and the ability to mentor engineers while driving engineering standards. What You Will Do • Design, build, and maintain scalable, reusable, and cost-efficient data pipelines and data products on Google Cloud Platform . • Develop resilient ETL/ELT pipelines supporting batch, near-real-time, and streaming data workloads across a modern Medallion architecture. • Build and optimize enterprise data models, including dimensional models and Star/Snowflake schemas . • Design and implement solutions using BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud Functions, Cloud Run, Workflows, and Terraform . • Optimize BigQuery performance, cost, reliability, and governance, including partitioning, clustering, query optimization, row-level security , and column-level security . • Build reusable APIs, services, and engineering utilities using Python, Docker, Kubernetes, Cloud Run, and CI/CD pipelines . • Partner with Data Architects, BI Developers, Data Scientists, and business stakeholders to translate business requirements into scalable, maintainable technical solutions. • Support the development and optimization of governed semantic layers and standardized business metrics in Looker and other reporting environments. • Establish and promote best practices for data quality, testing, observability, documentation, metadata, lineage, deployment, and operational support. AI-Enabled Data Engineering • Turn governed data into clear, natural-language answers that enable teams to explore insights safely and efficiently. • Design, build, and optimize Skills, AI Agents, and conversational workflows that translate business queries into accurate and understandable insights. • Develop and operationalize AI-enabled patterns such as Retrieval-Augmented Generation (RAG), Text-to-SQL, agentic workflows, and tool-based AI orchestration . • Connect governed BigQuery datasets and the Looker semantic layer to AI-enabled solutions, ensuring consistent metric definitions and trusted business logic. • Build robust tools, workflows, guardrails, monitoring, and evaluation frameworks to reduce hallucinations, improve answer quality, and help prevent unauthorized data exposure. • Partner with Data Science and AI teams to productionize AI and machine learning use cases by building reliable, governed, and scalable data foundations. Agile Delivery & Technical Leadership • Translate broad business epics into clear, developer-ready technical stories, tasks, and acceptance criteria. • Participate actively in Agile ceremonies, backlog refinement, sprint planning, design reviews, and iterative delivery. • Provide technical leadership through architecture reviews, engineering standards, code reviews, and delivery guidance. • Mentor Data Engineers and partner teams, supporting their technical growth and consistent adoption of engineering best practices. What We Are Looking For: Required Qualifications: • 7+ years of experience in data engineering, data architecture, analytics engineering, or related technical roles. • 4+ years of hands-on GCP experience , designing and implementing production-grade data solutions. • Strong hands-on expertise in: • BigQuery • SQL • Python • Dataflow and/or Dataproc • Pub/Sub • Cloud Composer • Cloud Run and/or Cloud Functions • Terraform and CI/CD toolchains • Strong experience designing and optimizing enterprise data models, ETL/ELT pipelines, and data platforms for structured, semi-structured, and unstructured data. • Proven experience with BigQuery performance tuning, partitioning, clustering, cost optimization, and secure data-access controls. • Strong proficiency in Looker semantic modeling , including governed metrics, explores, reusable dimensions, and consistent business definitions. • Demonstrated hands-on experience implementing AI-enabled data solutions, such as RAG, AI agents, Text-to-SQL, LLM-powered analytics, or conversational data experiences . • Experience developing secure and scalable APIs or services using Python and containerization technologies such as Docker and Kubernetes. • Experience working in Agile delivery environments and translating business needs into actionable technical requirements. • Strong communication, collaboration, and technical problem-solving skills. • Work authorization on a continuous, ongoing basis. Sponsorship is not offered for this role. Preferred Qualifications: • Strongly preferred: Experience working with Commerce data domains , including related data structures, metrics, reporting, and operational processes. • Experience with Power BI, DAX, Tableau, Looker Studio, or other enterprise BI and visualization platforms. • Experience with AI evaluation, prompt engineering, LLM observability, model safety controls, or responsible AI data-governance patterns. • Google Cloud Professional Data Engineer certification. • Exposure to ReactJS or development of lightweight internal web applications. As an integral part of our culture at L’Oréal, wellness is at our core. We not only offer a generous Benefits Package (Medical, Dental, Vision, 401K), we also offer flexible time off, work from home days, and a pension plan! Additionally, you will have access to company perks such as Makeup, Skincare, and Fragrance! Employees receive a stipend for L'Oréal products as well as VIP Access to L’Oréal’s Internal Shop for Discounted Products, and other perks such as Monthly Mobile Allowance, discounted gym memberships, and ERGs. Additional Benefits Information As Follows: Salary Range : $138,500 - $200,800 (The actual compensation will depend on a variety of job-related factors which may include geographic location, work experience, education, and skill level) • Competitive Benefit Package (Medical, Dental, Vision, 401K, Pension Plan) • Hybrid Work Policy (3 Days in Office, 2 Days Work from Home); Being present in the office three days a week is considered an essential function of all office-based roles for eligible full-time employees. • Flexible Time Off (Paid Company Holidays, Paid Vacation, Vacation Buy Program, Volunteer Time, Summer Fridays & More!) • Access to Company Perks (VIP Access to L’Oréal’s Internal Shop for Discounted Products, Monthly Mobile Allowance) • Learning & Development Opportunities (Unlimited Access to E-learnings, Lunch & Learn Sessions, Mentorship Programs, & More!) • Employee Resource Groups (Think Tanks and Innovation Squads) • Access to Mental Health & Wellness Programs 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. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to access job openings or apply for a job on this site as a result of your disability. You can request reasonable accommodations by contacting USApplicationAccommodation@support.lorealusa.com . If you need assistance to accommodate a disability, you may request an accommodation at any time. Our Safe Together Plan: Your safety is our highest priority. We will proceed with caution and adhere to enhanced protection standards to ensure our sites are safe for all employees. We must all operate with the shared responsibility for each other’s health & safety in mind.

Requirements

Must-haves

Job Title Cloud Data Engineering & AI Tech Lead
Division: Corporate IT, Data & AI
Location: New York, NY
Reports To: Data & AI – Domain Analytics Lead
L’Oréal is driving a massive Beauty Tech Transformation roadmap, designing and implementing next-generation Data Products to accelerate business growth across Commerce and Supply Chain.
Design, build, and maintain scalable, reusable, and cost-efficient data pipelines and data products on Google Cloud Platform .
Develop resilient ETL/ELT pipelines supporting batch, near-real-time, and streaming data workloads across a modern Medallion architecture.
Build and optimize enterprise data models, including dimensional models and Star/Snowflake schemas .
Design and implement solutions using BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud Functions, Cloud Run, Workflows, and Terraform .
Optimize BigQuery performance, cost, reliability, and governance, including partitioning, clustering, query optimization, row-level security , and column-level security .
Build reusable APIs, services, and engineering utilities using Python, Docker, Kubernetes, Cloud Run, and CI/CD pipelines .
Partner with Data Architects, BI Developers, Data Scientists, and business stakeholders to translate business requirements into scalable, maintainable technical solutions.
Support the development and optimization of governed semantic layers and standardized business metrics in Looker and other reporting environments.
Establish and promote best practices for data quality, testing, observability, documentation, metadata, lineage, deployment, and operational support.
AI-Enabled Data Engineering
Turn governed data into clear, natural-language answers that enable teams to explore insights safely and efficiently.
Design, build, and optimize Skills, AI Agents, and conversational workflows that translate business queries into accurate and understandable insights.
Develop and operationalize AI-enabled patterns such as Retrieval-Augmented Generation (RAG), Text-to-SQL, agentic workflows, and tool-based AI orchestration .
Connect governed BigQuery datasets and the Looker semantic layer to AI-enabled solutions, ensuring consistent metric definitions and trusted business logic.

Nice-to-haves

Strongly preferred: Experience working with Commerce data domains , including related data structures, metrics, reporting, and operational processes.
Experience with Power BI, DAX, Tableau, Looker Studio, or other enterprise BI and visualization platforms.
Experience with AI evaluation, prompt engineering, LLM observability, model safety controls, or responsible AI data-governance patterns.
Google Cloud Professional Data Engineer certification.
Exposure to ReactJS or development of lightweight internal web applications.

Application prep

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Keywords to mirror

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Platform: radancy
Effort: medium

Benefits

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Dental

Vision

401k

Wellness