Data Engineer / Analytics Engineer (Mid-Senior)
Summary
Data/Analytics Engineer in Lisbon building scalable ELT pipelines and dimensional models on GCP (BigQuery) for retail/e-commerce. Translates business requirements into dbt transformations, Looker dashboards, and data structures for decision-making. Stack: SQL, dbt, Python, Airflow, LookerML.
A critical role connecting business needs and technical data infrastructure. Responsible for transforming complex business requirements into robust, scalable data structures ready for analysis within the Google Cloud Platform ecosystem. This position emphasizes semantic modeling, ensuring data is prepared for autonomous business consumption and valuable for decision-making, while also adapting it for advanced uses such as AI agents.
2. Main Responsibilities
Data Preparation and Transformation: Design and implement efficient ETL/ELT processes.
BigQuery Development: Optimize queries, manage partitions, and apply business logic in the Data Warehouse.
Data Modeling: Apply dimensional modeling techniques (Star Schema/Snowflake).
Requirements Translation: Engage directly with stakeholders to capture needs and translate business questions into data models.
Quality and Validation: Ensure data consistency and integrity through rigorous testing and documentation.
Documentation and Knowledge Transfer: Communicate and document technical developments for training teams to facilitate the diffusion of created solutions.
3. Key Requirements
Advanced SQL proficiency
Experience with dbt (data build tool)
Experience in GCP (BigQuery)
Knowledge of Python
Proficiency in Looker / LookerML
Experience with orchestration tools (e.g., Airflow)
Dimensional data modeling
Experience in Retail / E-commerce
Version control (Git)
Google Cloud certifications
4. Nice to Have
Semantic Layer (LookerML): Development and maintenance of models in LookerML, defining dimensions and measures for self-service BI.