Summary
David Belais is a Staff Data Engineer in Portland, Oregon with nearly two decades of experience building resilient, testable data products and distributable Python libraries that power analytics and sustainability decisioning. He has led and mentored teams at Nike and Kroger to deliver production ELT/ETL pipelines, cross-platform ORM and filesystem tooling, and cost-saving orchestration frameworks spanning Databricks, Snowflake, EMR, Kafka, and Airflow. A pragmatic architect and hands-on coder, he authors type-annotated, well-tested SDKs, CLIs, and web APIs (FastAPI + SQLAlchemy) and champions CI/CD, schema versioning, and reproducible footprinting for environmental analytics. His work includes novel abstractions for multi-dialect SQLAlchemy support and an Airflow/Databricks/EMR deployment shim that materially reduced compute cost and latency for real workloads. Equally comfortable condensing ambiguous requirements into concrete roadmaps or diving into low-level data modeling, he blends product impact with engineering rigor. Outside typical metrics, he describes his craft as “engineering inorganic solutions for esoteric problems,” reflecting a taste for elegant technical problem-solving.
10 years of coding experience
9 years of employment as a software developer
Computer Science, Computer Science at Portland State University
Bachelor of Science (BS) Animation Interactive Technology Video Graphics and Special Effects, Bachelor of Science (BS) Animation Interactive Technology Video Graphics and Special Effects at The Art Institute of Portland
Fine Arts, Fine Arts at Loyola Marymount University