“The answer exists, but the data cannot reliably produce it.”
DATA + SCIENTIFIC COMPUTING
Data systems built for difficult questions.
Useful data engineering begins with the question the system must answer. I design databases, pipelines, search, retrieval, and computation around the workload—from operational reporting and AI context to scientific analysis at high-performance-computing scale.WHEN TO CALL
The pressure usually sounds like this.
“A workload has outgrown serial processing or manual analysis.”
“AI and application teams need one trustworthy data foundation.”
WHAT THIS WORK ENABLES
Turn fragmented data into a dependable application or decision system
Make computationally expensive workloads practical
Build data foundations that support both software and AI
CAPABILITIES
Data architecture and modelingETL and processing pipelinesRelational database engineeringSearch, retrieval, and indexingBioinformatics workflowsParallel and distributed processingHigh-performance computingOperational reporting and automation
RELEVANT PROOF
Experience behind the capability.
Genetic-sequencing software at research scale
Re-engineered bioinformatics software for parallel high-performance computing, contributing to internationally published Alzheimer’s research.
Data that drives operations
Hands-on work across transactional databases, reporting, ingestion, synchronization, recordings, search, APIs, and automation.
BRING THE HARD PROBLEM
Put that project back on the roadmap.
Tell me what needs to work, where you’re stuck, and what the system has to fit.
Talk to Mitch