Any Airflow project day 1, you can spin up a local desktop Kubernetes Airflow environment AND one in Google Cloud Composer with tested data pipelines(DAGs) 🖥️ >> [ 🚀, 🚢 ]

Run dbt serverless in the Cloud (AWS)

dbt (data build tool) projects targeting AWS analytics services (redshift, glue, emr, athena) and open table formats

DWH powered by Clickhouse and dbt

...an automated data pipeline that retrieves cryptocurrency data from the CoinCap API, processes and transforms it for analysis, and presents key metrics on a near-real-time dashboard

dbt Core and Microsoft Azure: end to end example of using dbt Core and Microsoft Azure

A data engineering project with dbt, Docker, Kestra, Terraform, GCP and Looker.

Completely Serverless ELT platform that can be used for any integration. We just so happen to focus on threat intelligence right now :)

Deploy an open source and modern data stack in no time with Terraform

Deploy an airbyte instance with dbt models in Google Cloud in 5 minutes

Playing with DBT on Databricks

Final project for DataTalks.Club Data Engineering bootcamp

FlightRadar ELT pipeline on GCP

Data pipeline for collecting, transforming, storing, and visualizing job market data to analyze Data Engineering opportunities in France.

The ELT pipeline we’ve developed leverages several Google Cloud Services including Google Cloud Storage (GCS), BigQuery, Pub/Sub, Cloud Workflows, Cloud Run, and Cloud Build. We also use dbt for data transformation and Terraform for infrastructure as code.

Skytrax airline reviews data platform — Snowflake, dbt, Terraform, AWS (S3, CloudFront, IAM OIDC), GitHub Actions slim CI/CD with zero-copy cloning, SQLFluff linting, and Kimball star schema dimensional modeling.

Production-grade financial data infrastructure platform on GCP — BigQuery, BigTable, Pub/Sub, GKE, Airflow, dbt, Terraform

Repository to analyse customer reviews from Sephora products

Refera Challenge (Part 2): dbt transformations for the data warehouse built on AWS Athena. This project models the raw data from the data lake into a star schema with fact and dimension tables. The transformations are deployed via AWS Lambda and scheduled with CloudWatch. Infrastructure is managed with Terraform.

Test authorized views created by the combination of dbt and terraform