Pipelines, streaming and cloud data platforms.
A data engineer building the pipelines and platforms everything downstream depends on.
For the past three years I've built the pipelines other people's work sits on top of. Batch and streaming, across healthcare claims, industrial sensor data, job-market data and university research.
At Cigna I run a HIPAA-compliant ELT pipeline over 15TB of claims a day and a Kafka eligibility service answering in under two seconds. Before that, a serverless ingestion layer at Maryland, and a Databricks lakehouse at Siemens that put batch and streaming behind one door for 100+ analysts.
The tools change. What hasn't is the approach: know where the data came from, assume it is wrong until it proves otherwise, and make the thing fail loudly rather than quietly.
A pipeline nobody trusts isn't finished.
An agentic trip planner that orchestrates seven MCP servers through Claude, pulling live flights, hotels and events into a single request. I load-tested EC2 against ECS Fargate at 50 to 100 concurrent users; Fargate matched EC2's 460 RPS on half the compute.
A YOLO vision pipeline that spots wildlife on farmland in real time and fires a non-lethal deterrent matched to the animal, so nobody has to watch a monitor. Hardware prototype built and tested alongside the model.
End-to-end pipeline: live BTC collection, ARIMA and XGBoost models at around 85% accuracy, automated ETL, and Qlik Sense dashboards giving real-time visibility into volatility. Cut the manual reporting effort by 40%.
A full analytics pipeline over a multifamily portfolio: SQLite to engineered features to five business reports, a seven-sheet Excel workbook and Power BI. Surfaced $2.14M of annual loss-to-lease and a 26-point occupancy gap. The data is synthetic, generated with Faker. This was built to demonstrate the pipeline, not to report on a real client.
Fig. 003 · Four projects, ordered by how much I learned rather than by date.
Open to full-time data engineering and data platform roles. The inbox is always on.
An AI answering as me, from my real resume and projects.
