As Data Platform Engineer you are responsible for building and maintaining the data models that G-Star's Finance, Retail, Ecommerce and Wholesale teams rely on. This includes developing and documenting models on our Google Cloud platform, implementing data quality tests, and managing the performance and running cost of what you build. You work closely with stakeholders across the business to translate their reporting needs into reliable, well-documented data products, within a small team where you take direct ownership of your work.
What you'll do
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Build and maintain data models in Dataform on BigQuery, from a business question through to a table someone reports on
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Own the models in your area: their documentation, their data quality and their running cost
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Write the tests and assertions that catch problems before the business notices them
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Keep the platform's cost under control — we measure before and after every change
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Work with colleagues in Finance, Retail, Ecommerce and Wholesale to turn reporting needs into clear specifications, and build so they can serve themselves next time
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Support the platform around the models: ingestion via Airbyte, infrastructure in Terraform, orchestration on Kubernetes
What we're looking for
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Three or more years building data pipelines in production
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Strong SQL — you should be able to look at a query and explain why it's expensive
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A cloud data warehouse in production: BigQuery preferred, Snowflake or Databricks fine
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A transformation framework such as Dataform or dbt, and Git as a daily habit
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Enough Python to automate the things that shouldn't need a person
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You document as you go, and you're comfortable owning something outright in a small team
Nice to have
SAP or another ERP as a source system · Terraform, Kubernetes or CI/CD · Tableau or a comparable BI tool · retail or ecommerce data