April 16, 2024, 8:26 p.m. | Λ\: Clément Bosc

DEV Community dev.to

If you work with Google Cloud for your Data Platform there are chances that you use BigQuery and run your Data pipelines transformations in a ELT manner: using BQ query engine to run transformations as a series of SELECT statements, one after another. Indeed over the last few years, ELT and tools like DBT or Dataform have been the de-facto standard for running and organizing your Data transformations at scale.


Theses tools, that we may group under the “SQL orchestration …

bigquery cloud data dataops data pipelines data platform elt experimental google google cloud googlecloud graph indeed pipelines platform query query engine series sql theory tool work

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US