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Senior Analytics Engineer - Data & Analytics
senior · Data Science & Analytics
Unleash Your Potential at L'Oréal's Beauty Tech!
Who Are We?
For 115 years, L’Oréal, the world’s leading beauty player, has devoted itself to one thing only: fulfilling the beauty aspirations of consumers around the world.
For more than a century, L’Oréal has devoted itself solely to one business: Beauty. Present in 150 countries across five continents and with €42 billion consolidated sales, L'Oréal is the global industry leader. With 37 global beauty brands across four divisions, L’Oréal offers beauty for each covering all beauty categories and catering to all beauty desires. With the acquisition of the Australian brand Aēsop in 2023, the Group continues to expand its portfolio through targeted acquisitions as part of its drive to create the future of beauty.
Today, L’Oréal includes more than 2,000 tech professionals and is constantly growing. Beauty Tech is changing the game and leading the shift towards new consumer realities and a digital disruption. Championing Beauty Tech, we invent the beauty of the future while becoming the company of the future.
Beauty Tech is how we know our consumers intimately, augmenting their beauty journeys with unparalleled diverse and sustainable experiences. Beauty Tech equips the Group with the key assets it needs to conquer this new world, where Tech has become strategic. With this ambition, L’Oréal continues to recruit diverse, innovative, skilled and passionate minds in different tech domains such as Data, Digital, Cloud, Cyber Security, IT Architecture, DevOps, Applications and Infrastructure.
A Day in the Life of A Senior Analytics Engineer – Data & Analytics!
- Data Transformation: Architect and build the "Transformation Layer" in BigQuery, turning raw data into high-quality, usable datasets for advanced analytics use cases.
- Support Advanced Analytics: Collaborate with Data Scientists and Analysts to create specialized datasets for predictive modelling, optimization projects, and executive dashboards.
- Ensure Data Trust: Implement testing and documentation within the transformation pipeline to ensure data accuracy and reliability across the SAPMENA region.
Strategic Bridge: Act as the technical translator between business-facing teams and the raw data infrastructure.
In this role, You will..
- Translating Business Context into Code: Collaborate with business stakeholders across North Asia and SAPMENA to understand the "Why" behind data requests. You will be responsible for translating these business contexts into robust technical logic.
- Building Advanced Analytics Datasets: Design and develop the logic that transforms raw BigQuery data into curated datasets. These datasets will power high-impact use cases, including machine learning models, optimization engines, and strategic dashboards.
- Modeling for Performance: Apply best practices in data modelling to ensure that transformed datasets are not only accurate but also performant and cost-effective within the BigQuery environment.
- Engineering Excellence: Move analytics beyond "just scripts" by applying software engineering principles. This includes using Git for version control, writing data tests to catch upstream changes, and documenting the lineage of datasets.
- Collaborative Integration: Work closely with the Visualization team and Data Science teams to ensure the data marts you build are seamlessly integrated into their specific tools and semantic models.
- Framework Adherence: Operate within the BTDP (Beauty Tech Data Platform) framework, ensuring all developments meet L’Oréal’s global standards for data security, access management, and architectural integrity.
What are we looking for?
Must Have (Core Competencies):
- Expert SQL: Mastery of SQL is essential. You must be able to write, debug, and optimize complex queries (CTEs, Window Functions, etc.) to handle large-scale datasets.
- Data Modelling: Strong expertise in Dimensional Modelling, Star Schemas, and designing efficient data structures that balance performance with usability.
- Modern Transformation Tools: Previous experience with dbt (data build tool) is critical for managing the transformation layer.
- Cloud Ecosystem: Experience in developing high performant pipelines leveraging Google Cloud Platform (GCP) and BigQuery architecture.
- Version Control (Git): Proficiency in Git and version control best practices to ensure collaborative and auditable code development
Good to Have (Advantageous):
- Programming: Proficiency in Python for data manipulation and automating analytical workflows.
- DevOps/Infra: Understanding of CI/CD pipelines (Cloud Build) and Infrastructure as Code (Terraform).
- Downstream Context: Experience in how data is consumed for Visualisation (e.g., Power BI) or Advanced Analytics (e.g. Data Science models/Optimization engines)
Business Translation: Previous experience in contextualizing requirements with business stakeholders and translating those needs into clean,
What’s In It for You?
- Working with cutting edge Technology, empowering employees with new age learning, global exposure, and opportunities to build future-ready careers.
- A flexible and modern workplace, enabling teams to perform at their best through a smart hybrid model that supports balance and autonomy. A 3 Day in Office, 2 Day Work from Home setup.
- Employee support at every life stage, with inclusive and progressive parental policies that help individuals and families thrive.
- Holistic wellbeing offerings - personalized health benefits and strong mental wellness support to ensure employees feel their best.
- Reward and Recognition opportunities, long-term incentives, and opportunities to share in L’Oréal’s collective success.
- L'Oreal is an Equal Opportunity Employer and takes pride in a diverse environment
We would love to find out more about you as a candidate and we do not discriminate in recruitment, hiring, training, promotion, or other employment practices. The beauty we find in our differences gives us the freedom to go beyond. That’s the beauty of L’Oréal.