Data Engineering | McHugh Analytics
Reliable data pipelines, warehouses, and platforms that give your business a foundation it can actually build on.
Overview
Most growing businesses have data — but it’s scattered, inconsistent, or stuck in systems that don’t talk to each other. Before you can get value from analytics or AI, you need a solid data foundation.
I build the pipelines, warehouses, and platforms that turn raw, messy data into something reliable and queryable. No over-engineering, no unnecessary complexity — just infrastructure that does what it needs to do.
What I can build
- Data pipelines — ingestion, transformation, and loading (ELT/ETL) from your source systems
- Data warehouses and lakehouses — structured storage designed for the queries you actually run
- Data platform architecture — design and build a coherent platform from source to consumption
- Data quality and observability — monitoring and validation so you know when something breaks
- API and event stream integration — connecting real-time data sources into your data layer
Technologies
Python, dbt, Apache Spark, Airflow, AWS (Redshift, Glue, S3), Azure (Synapse, Data Factory), BigQuery, Snowflake, PostgreSQL, and more. I’ll work with what you have, or recommend the right stack for where you’re going.
The outcome
A data layer your team can trust — one that loads reliably, surfaces clean data, and doesn’t require heroics to maintain.