Data Pipelines & ETL
Data is useless if it's stuck in source systems. We build robust, automated Data Pipelines (ETL/ELT) that extract data from APIs, databases, and flat files, transform it into usable formats, and load it securely into your central data warehouse.
Service Overview
ELT Architecture
Extracting and Loading raw data first, then Transforming it inside the powerful data warehouse using dbt.
API Integrations
Building custom Python connectors to pull data from niche SaaS applications.
Pipeline Orchestration
Using Apache Airflow or Dagster to schedule, monitor, and retry complex data workflows.
Key Benefits
Fresh Data
Ensure business dashboards are powered by up-to-the-minute data, not yesterday's exports.
Automated Reliability
Eliminate manual Excel exports and scripts that break constantly.
Clean Data Models
Transform messy raw data into clean, business-ready models automatically.
Our Process
Source Mapping
1-2 WeeksIdentifying all data sources, API limits, and required sync frequencies.
Ingestion Build
2-4 WeeksSetting up Fivetran or coding custom Python scripts to move raw data.
Transformation & Modeling
3-5 WeeksWriting dbt (SQL) models to clean, join, and aggregate the data for reporting.
Industries Served
Marketing Agencies
Piping data from Facebook, Google Ads, and CRMs into unified dashboards.
SaaS Platforms
Moving production database replicas into analytics environments.
Technologies We Use
FAQ
What is the difference between ETL and ELT?
What happens if an API source goes down?
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