Ryan's Portfolio

Data engineering for me is about building reliable systems that move and transform data without constant babysitting. My toolkit centers on Python, SQL, AWS Lambda, and DBT.

I prefer building event-driven architectures over traditional cron-based scheduling because I've seen the mess that happens when data scales. In previous roles, we constantly fought "timing wars" where downstream jobs would fail because upstream jobs took longer than expected. By shifting to event-driven triggers (SNS/SQS), I ensure that cascading processes only start when the data is actually ready, eliminating race conditions and silent failures.

I also enjoy building tools that simplify data entry for other developers. For instance, I created a "Touchpoint Framework" that allowed teams to define complex data sources via simple config files (mapping dates, amounts, and descriptions). The system automatically handled the heavy lifting, validating and unioning these disparate sources into a single, clean master table for analysis.