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Joseph Steger

@josephsteger

I build Microsoft Fabric lakehouses and resilient data pipelines that improve enterprise reporting, reliability, and cost efficiency.

United States

Message

I've built unified Microsoft Fabric lakehouses at Pinnacle Software Group, standardizing Bronze-to-Gold Delta pipelines across 14 client tenants and reducing reporting latency by 48%. I also developed secure Python MCP servers and REST ingestion frameworks handling 42 TB of monthly system logs.

Previously, I modernized 65 enterprise ETL workflows at Vertex Digital Systems and built Python, SQL, and PostgreSQL data services at Nava Benefits. I focus on reusable engineering standards, secure multi-tenant platforms, automated testing, and data systems that perform reliably at scale.

Experience

Work history, roles, and key accomplishments

Senior Data Engineer

Pinnacle Software Group

May 2024 - Jun 2026 (2 years 1 month)

Architected a unified Microsoft Fabric lakehouse using medallion architecture, standardizing Bronze-to-Gold Delta pipelines across 14 client tenants to reduce cross-tenant reporting latency by 48%. Built secure MCP servers in Python with OAuth2 authorization and prompt injection filters, cutting automated agent query execution failures by 59%.

Senior Data Engineer

Vertex Digital Systems

Mar 2019 - Apr 2024 (5 years 1 month)

Migrated 65 legacy enterprise ETL workflows into Azure Synapse and Azure Data Factory, establishing modular micro-batch processing patterns that shortened nightly batch windows from 5h to 72m. Engineered Python-driven REST extraction microservices with dynamic token pagination and circuit-breaker logic, maintaining uninterrupted 24/7 ingestion across 30+ third-party cloud API services.

Azure Synapse Azure Data Factory Python REST APIs Azure Purview Terraform Azure DevOps SQL Data Warehouse ETL ELT Infrastructure as Code CI CD Performance Optimization Data Governance

Data Engineer | Python Developer

Nava Benefits

Jun 2016 - Feb 2019 (2 years 8 months)

Developed robust Python scripts to ingest and normalize policyholder insurance claims from disparate partner SFTP servers, automating record ingestion and eliminating 15+ manual weekly data loads. Engineered automated data validation scripts with Python and SQL to verify claims adjudication rules, reducing downstream reconciliation errors and schema mismatches across policy files by 41%.

Python SQL PostgreSQL REST APIs Data Pipelines ETL ELT Data Validation Performance Optimization