The Modern Data Engineering Stack

The Modern Data Stack Has Evolved

The modern data stack is no longer just about tools. It's about composable architectures that let you swap components as your needs evolve.

Ingestion Layer

Tools like Fivetran, Airbyte, and custom Python scripts handle data extraction. The key is reliability and monitoring, not just connectivity.

Transformation Layer

dbt has become the standard for SQL-based transformations. It brings software engineering practices like version control, testing, and documentation to data transformation.

Storage Layer

Cloud data warehouses (Snowflake, BigQuery, Databricks) have made storage cheap and compute elastic.

Orchestration

Airflow remains popular, but newer tools like Dagster and Prefect offer better developer experience and observability.

What We Recommend

There's no one-size-fits-all. We help clients evaluate their team maturity, data volume, and budget to recommend the right stack for their context.