Patrick Beekman is a Lead Data Engineer based in Berkeley with nine years of experience designing and optimizing data platforms and ELT pipelines for product and analytics teams. He has a track record of driving large-scale geospatial and retail data projects—cutting core pipeline runtime 10x and costs 15x while standardizing semantic versioning, deployments, and cross-cloud migrations. Comfortable across Kubernetes, BigQuery, Apache Beam, Celery and serverless tools, he builds scalable tooling that empowers Data Scientists and engineers to deliver on cadence. Patrick’s background in academic research and hobby projects—automating bee-activity labeling and attempting CNN/autoencoder classifiers—reveals a persistent focus on noisy, imbalanced data problems and creative data-collection tooling. He balances pragmatic production delivery with experimentation, having shipped reliable quarterly releases and reusable packaged tooling for engineering teams. Fun fact: his affinity for bees informs both his research and a people-centered engineering approach that values democratic, observable systems.
9 years of coding experience
9 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at Appalachian State University
Associate’s Degree Computer Science, Associate’s Degree Computer Science at Wake Technical Community College
Segment the stigma from images of squash plant flowers
Contributions:2 PRs, 20 pushes, 6 branches in 5 months
plantpythonsquashstigmaflowers
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