Success Story
Building a Scalable Data Warehouse & Orchestration System
Lucca
November 2024
Designed and implemented a data warehouse from scratch on Google Cloud Platform, integrating dbt, Airbyte, and Dagster for robust data orchestration and infrastructure-as-code.
Infrastructure from Zero
Building enterprise data foundations from the ground up
Technologies Used
GCP
BigQuery
Python
Airbyte
Dagster
Docker
PySpark
Terraform
Cloud Functions
dbt
GitHub Actions
The Challenge
- The client had no existing data warehouse infrastructure, limiting their ability to centralize and analyze data effectively.
- There was a need to implement modern data transformation (dbt) and ETL tools (Airbyte) with proper CI/CD and orchestration.
- Infrastructure setup needed to be automated and managed as code (IaC).
- Provided technical leadership to Analytics Engineers.
The Solution
- Created a data warehouse from scratch on Google Cloud Platform (BigQuery, Cloud Storage).
- Implemented dbt for data transformations with CI/CD on GitHub Actions.
- Deployed Airbyte on Google Compute Engine for ETLs, configuring extractions in low-code.
- Set up Terraform configurations for IaC, covering Airbyte and GCP resources (IAM, datasets, VMs).
- Orchestrated workflows (Airbyte, dbt, Python scripts) using Dagster/Airflow and Docker.
- Managed and provided technical support/training to 3 Analytics Engineers.
Results & Impact
- Established a robust, scalable, and automated data foundation on GCP, enabling comprehensive data analytics.
- Empowered analysts with dbt for efficient and version-controlled data transformations.
- Streamlined ETL processes and ensured infrastructure consistency through automation.
- Contributed to the growth and capability of the internal data team.
Project Summary
ClientLucca
CompletedNovember 2024
CategoryData Engineering
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