Job objectives:

- 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.

Role & responsibilities

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, technical code.

Job description:

- 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 workplace.
- 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 LOrals global standards for data security, access management, and architectural integrity.

📌 LOreal is Hiring For GCP Data Engineer with Gen Ai (Hyderabad)
🏢 Loreal India
📍 Hyderabad