Jordan Wolinsky
Chicago, Illinois, United States
Summary
🤩
Rockstar🎓
Top SchoolJordan Wolinsky is a pragmatic software engineer with roughly a decade of hands-on experience building backend systems, data pipelines, and production tooling across startups and enterprise teams. Currently finishing a B.S. in Computer Science at the University of Maryland and formerly an engineer at Rally Health and Zephyr AI, Jordan has shipped database migrations, refactored front-end/back-end integrations, and improved test and caching resilience in production. He contributes to notable open-source projects like DataHub and Dagster, adding AWS ingestion features, metadata emitters, and lineage integrations that bridge orchestration and metadata systems. Comfortable across Scala, Python, Kubernetes, AWS, and CI tooling, he brings a systems-minded approach to reliability and observability. An unusual strength is his knack for operational scripting and automation—from election-night web scrapers to serverless Slack bots—that turns ad-hoc needs into repeatable, maintainable services.
10 years of coding experience
3 years of employment as a software developer
Bachelor’s Degree, Computer Science, Mathematics Minor, Bachelor’s Degree, Computer Science, Mathematics Minor at University of Maryland
English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (29)
dagster10
data-pipelines10
python10
data-engineering10
kafka10
metadata10
data-ingestion10
aws10
amazon-s310
aws-s310
orchestration10
orchestra10
data-pipeline10
data-integration10
s3-bucket10
Programming languages (6)
Github contributions (5)
datahub-project/datahub
Apr 2022 - Aug 2022
The Context Platform for your Data and AI Stack
Role in this project:
Back-end Developer
Back-end DeveloperContributions:17 reviews, 5 commits, 5 PRs in 3 months
Contributions summary:Jordan focused on enhancing the data ingestion pipeline within the DataHub project. Their contributions include implementing AWS-related features, such as handling temporary credentials for AWS profiles within the ingestion process. They also added the capability to ingest tags from S3 buckets and objects when using AWS Glue and S3 Data Lake Ingest Jobs, enhancing metadata management. Additionally, they fixed a bug related to profiling S3 data when using table placeholders and exposed the catalog name in Athena source.
aimetadatadatahubdata-catalogdata-discovery
dagster-io/dagster
Oct 2021 - Jul 2022
An orchestration platform for the development, production, and observation of data assets.
Role in this project:Data Engineer
Data EngineerContributions:4 reviews, 5 commits, 2 PRs in 9 months
Contributions summary:Jordan primarily focused on enhancing and integrating the Dagster platform with Datahub, a metadata management system. Their contributions include implementing the integration of Datahub emitters, specifically for REST and Kafka, enabling data lineage and metadata exchange. They worked on adding resources and configurations for these integrations, including testing, and also addressing documentation and build-related issues. These changes significantly expanded Dagster's capabilities for data governance and metadata management.
operationpythonobservationschedulermetadata
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