Most data stacks look fine until they don't — pipelines failing silently, warehouses that drift, and analytics layers nobody trusts by quarter-end. I build the infrastructure that holds. The same standard demanded by health plan compliance, Fortune 500 scale, and U.S. military infrastructure.
I'm a Senior Data Engineer with five years of professional experience and a Master's in Data Analytics from Penn State. I specialize in data infrastructure that runs in production — not just proofs of concept.
I've built data infrastructure where the margin for error is effectively zero — health plan integrations handling PHI, enterprise retail systems processing at Fortune 500 scale, and modernization projects for the U.S. Army, Navy, and Air Force. That experience shapes how I approach every pipeline, every data model, every handoff.
Most companies that need serious data engineering aren't ready to hire for it full-time. That's exactly where I work best — senior-level infrastructure, scoped to what you need, without the commitment of a permanent hire.
End-to-end data engineering from greenfield architecture to production hardening.
End-to-end ETL/ELT design and implementation — raw ingestion through analytics-ready layers. Medallion architecture, incremental load patterns, and lineage tracking built in from day one, not bolted on later.
Architecture and implementation for lakehouses and warehouses built to scale — schema design, partition strategy, access patterns, and performance tuning. Pick your platform; I've built production systems on all of them.
Legacy system modernization and cloud migrations — Oracle, on-prem databases, and aging pipelines moved to modern cloud-native infrastructure without disrupting what's already running.
Data infrastructure for industries where PHI, PII, access controls, and audit trails aren't optional — healthcare, defense, and government. Where the cost of getting it wrong is real. HIPAA-compliant pipelines, role-based access, and documentation built to withstand scrutiny.
Turning raw warehouse data into reliable, business-facing models. dbt semantic layer, dimensional modeling, and self-service BI enablement — so analysts stop waiting on engineering for every query.
An embedded senior data engineer for teams that need ongoing infrastructure work but aren't ready to hire full-time. Flexible scope — weekly hours, sprint-based, or project retainer. Structured so your team owns what gets built.
Real production systems, real constraints, real stakes.
Clinical data infrastructure at a health tech company building remote monitoring platforms. HIPAA-compliant pipelines, PHI/PII handling, health plan integrations, and clinical data systems on GCP — in an environment where data quality isn't optional.
Enterprise-scale data pipelines, real-time processing, and high-volume transaction systems for Fortune 500 retail. The kind of scale that breaks naïve pipeline designs — and teaches you what resilient ones look like.
Data systems for U.S. military branches and federal agencies. Secure infrastructure, legacy modernization, and the compliance rigor that defense data environments require. Engagements across branches of the Armed Forces.
No black boxes. Here's exactly what to expect.
A working session to understand your stack, your constraints, and what done actually looks like for your business. No assumptions, no templates applied without context.
A scoped engagement plan with clear deliverables, timeline, and a definition of done. Fixed-scope or retainer — whichever fits the actual work.
Hands-on engineering with documentation throughout. You see progress incrementally, not just a final delivery dropped at the finish line.
Full documentation, runbooks, and knowledge transfer. Your team owns what was built. Continued engagement is available — not required.
If you're building something that needs to work at scale — or inheriting something that doesn't — let's talk. I work with companies that treat data infrastructure as a serious business investment, not an afterthought.