Retail & E-Commerce Data Engineer

About the role

The candidate will be responsible for transforming complex business needs into robust, scalable, and analysis‑ready data structures within the Google Cloud Platform ecosystem. The primary focus lies in semantic interpretation and modeling—ensuring data is prepared for autonomous business consumption and served as valuable assets for decision‑making. Additionally, this position involves adapting data structures for advanced use cases, such as AI agents.

Key responsibilities

• Data Preparation & Transformation: design and implement efficient ETL/ELT processes.
• BigQuery Development: optimise queries, manage partitions, and apply business logic within the data warehouse.
• Data Modeling: apply dimensional modelling techniques (star schema / snowflake).
• Requirements Translation: work directly with stakeholders to capture needs and turn business questions into data models.
• Quality & Validation: ensure data consistency and integrity through testing and thorough documentation.
• Documentation & Knowledge Sharing: explain and document technical developments for training teams and smooth adoption.
• Semantic Layer (LookerML) – Nice‑to‑Have: develop and maintain LookerML models, defining dimensions and measures for self‑service BI.

Required profile

• Strong comprehension: quickly understand business dynamics and translate them into metrics and KPIs.
• Stakeholder interaction: experience working with product, finance or operations departments.
• Critical thinking: challenge incomplete or inconsistent requirements.
• Analytical mindset: focus on problem‑solving and delivering high‑quality outcomes for end users.

Required skills

• Advanced proficiency in SQL
• Experience with GCP (BigQuery)
• Proficiency in Looker / LookerML
• Dimensional data modelling
• Version control (Git)
• Experience with dbt (data build tool)
• Knowledge of Python
• Orchestration tools (e.g., Airflow)