ETL Consulting

Design, build, and modernize production-grade ETL pipelines that move data reliably across systems.

SaaS Companies Operations-Heavy Businesses Analytics Departments

Overview

Extract, Transform, Load remains the backbone of every analytics practice and every operational integration. We design ETL systems that are idempotent, observable, and cheap to run — whether you’re moving from a spreadsheet to your first warehouse or replacing a legacy Kettle PDI estate with a modern Airflow + dbt + Snowflake stack.

Reference Architecture

flowchart LR
Sources[("Source Systems<br/>(APIs, DBs, Files)")] --> Ingest["Ingestion<br/>(Airflow / Fivetran)"]
Ingest --> Raw["Raw Zone<br/>(S3 / ADLS)"]
Raw --> Stage["Staging<br/>(Snowflake / Databricks)"]
Stage --> Transform["Transform<br/>(dbt)"]
Transform --> Marts["Marts<br/>(Star Schema)"]
Marts --> Consumers["BI, ML, Apps"]

Engagement Model

Typical engagements run 6–16 weeks and follow a discover → design → build → harden → handoff cadence. We embed alongside your team rather than operating in isolation, so the knowledge stays in-house when we leave.

What's Included

Source-system audit and ingestion strategy
Idempotent, replayable transformation pipelines
Data quality validation and observability hooks
Legacy ETL (Kettle PDI / Pentaho) migration to a modern stack
Production runbooks, on-call documentation, and team handoff

Technologies

Snowflake
Databricks
PostgreSQL
Apache Airflow
dbt
Python
Kettle PDI

Related Services

Data Pipeline Modernization
Replace fragile cron jobs and legacy ETL with declarative, observable pipelines on Airflow and dbt.
Data Integration Services
Connect disparate systems into a unified data ecosystem — APIs, streaming, master data, and cross-platform sync.
Analytics Engineering
Turn raw warehouse data into trusted, well-modeled datasets that analysts, executives, and downstream apps can rely on.

Ready to discuss your etl consulting needs?

Schedule a Consultation