Cloud Data Platform Engineer — BigQuery & Dataform

G-STAR RAW; Amsterdam; Presencial; EUR 90.000 - 120.000; Jornada completa

Descripción de la vacante

G-Star RAW is seeking a Data Platform Engineer to build and maintain data models used by Finance, Retail, Ecommerce and Wholesale teams on Google Cloud.

You will own models from design to documentation, ensure data quality, manage running costs, and write tests. Collaborate with stakeholders to translate reporting needs into reliable data products, in a small team with clear ownership. You will optimize pipelines, monitor performance, and contribute to cost-aware architecture.

Formación

• 3+ years building data pipelines in production.
• Strong SQL and ability to explain why a query is expensive.
• Cloud data warehouse in production (BigQuery preferred).
• A transformation framework such as Dataform or dbt, and Git daily use.
• Some Python for automation.
• Documentation and ownership in a small team.

Responsabilidades

• Build and maintain data models in Dataform on BigQuery, from a business question through to a table reported on.
• Own the models’ documentation, data quality, and running cost.
• Write tests and assertions to catch problems before the business notices them.
• Keep the platform’s cost under control and measure changes.
• Collaborate with Finance, Retail, Ecommerce and Wholesale to translate reporting needs into clear specifications.
• Support ingestion via Airbyte, Terraform infrastructure, and Kubernetes orchestration.

Conocimientos

Strong SQL

Python

Documentation

Stakeholder collaboration

Data modeling

Herramientas

BigQuery

Dataform

dbt

Airbyte

Terraform

Kubernetes

Git

Descripción del empleo

G-Star RAW is seeking a Data Platform Engineer to build and maintain data models used by Finance, Retail, Ecommerce and Wholesale teams on Google Cloud.

You will own models from design to documentation, ensure data quality, manage running costs, and write tests. Collaborate with stakeholders to translate reporting needs into reliable data products, in a small team with clear ownership. You will optimize pipelines, monitor performance, and contribute to cost-aware architecture.