Kamil Piechowiak
Datastore Research Engineer
Greater Poland Voivodeship
Summary
🤩
Rockstar🎓
Top SchoolKamil Piechowiak is a Datastore Research Engineer with six years of experience building high-performance data and ML systems, currently contributing to Pathway on stream processing and temporal query features. His background blends academic research in machine learning and optimization with production roles at Meta/Facebook, giving him a strong footing in both experimental and operational data engineering. At Pathway he has shaped core operators, temporal joins, and Python API ergonomics for a framework used in real-time analytics and LLM pipelines. Comfortable across research and engineering, he brings a knack for turning complex temporal and numerical semantics into robust, well-documented implementations. Based in Greater Poland, he pairs a master’s in Artificial Intelligence with hands-on open-source impact in a prominent Python ETL project.
6 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Poznan University of Technology
Github Skills (16)
etl10
stream-processing10
rust10
python10
data-processing10
data-pipelines9
data-structure9
data-pipeline9
datastructures-algorithms9
data-structures9
algorithms9
type-checking8
machine-learning-algorithms8
typehinting8
algorithm8
Programming languages (6)
Github contributions (5)
pathwaycom/pathway
May 2023 - Jan 2025
Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
Role in this project:
Backend Developer
Backend DeveloperContributions:27 comments, 9 issues in 1 year 8 months
Contributions summary:Kamil primarily contributed to the core functionality of the Pathway framework, focusing on implementing and refining operators for stream processing, data transformations, and query evaluation. They added support for tuple comparisons and contributed to the design of temporal operations such as interval joins and asof joins, introducing features like handling zero-length intervals and incorporating temporal behavior. The user was also involved in implementing numerical operations, such as absolute value calculations, and enhancing the Python API for better integration and usability.
batch-processingdata-analyticsdata-pipelinesdata-processingdataflow
pathwaycom/llm-app
Jul 2023 - Dec 2024
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
Contributions:28 reviews, 5 PRs, 5 pushes in 1 year 4 months
chatbothugging-facellmllm-localllm-prompting
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.