Matthew Osgood

I'm a Data Engineer with 3+ years building production ETL/ELT pipelines and large-scale data-processing systems in financial services. I specialize in PySpark, Microsoft Fabric, and Delta Lake architectures across bronze/silver/gold lakehouse layers — cleansing, deduplicating, and transforming raw source data into reportable, well-modeled (SCD Type 2) datasets.

Much of my work is performance optimization — partitioning, clustering, and indexing to drive down compute cost — and partnering directly with business stakeholders to translate their needs into reliable data products. I've driven automation initiatives that saved roughly $150K per month and cut 59 Spark cold starts from a high-cost refresh pipeline.

Outside of the data stack, I ship full-stack products end-to-end with Next.js, Supabase, and Stripe, and I host open-source LLMs with RAG and vector search to power internal automation. I'm passionate about building practical, scalable systems that make a measurable impact.

Technical Skills