Ephrim Stanley
GenAI at Point72
Jersey City, New Jersey, United States
Summary
🤩
Rockstar🎓
Top SchoolEphrim Stanley is a seasoned infrastructure and data platform engineer with 11+ years building cloud-native systems and production-ready data tooling, now focused on GenAI at Point72. He combines a pragmatic drive for short-term delivery with long-term platform strategy, consistently automating builds, tests and deployments as evidenced by Docker installers and CI workflows contributed to the FINOS Legend project. At Goldman Sachs he progressed from middleware and application infrastructure to senior R&D roles in digital assets and data engineering, mentoring teams as an independent interviewer and career coach. His backend and DevOps work spans BigQuery, Snowflake, Databricks and Redshift integrations, reflecting deep familiarity with large-scale data systems and SQL execution plumbing. Based in Jersey City, he pairs an MS in Computer Science with hands-on experience modernizing identity, connection pooling and deployment pipelines in complex enterprise environments. Colleagues rely on him as a bar-raiser who brings both operational rigor and thoughtful engineering trade-offs to ambiguous problems.
10 years of coding experience
11 years of employment as a software developer
Master of Science (MS) Computer Science, Master of Science (MS) Computer Science at Indiana University BloomingtonBachelor of Engineering (BE) Computer Science, Bachelor of Engineering (BE) Computer Science at Vellore Institute of Technology
Tamil
Github Skills (23)
github-ci10
docker10
bigquery10
authentication10
user-authentication10
bash10
dockers10
java10
cicd10
javas10
githubaction-workflow10
relational-databases10
snowflake9
postgresql9
aws-redshift9
Programming languages (6)
Github contributions (5)
finos/legend
Feb 2021 - Dec 2022
The Legend project
Role in this project:
DevOps Engineer
DevOps EngineerContributions:63 reviews, 23 commits, 81 PRs in 1 year 10 months
Contributions summary:Ephrim focused on enhancing the repository's deployment and integration capabilities. They implemented a Docker installer and updated documentation, along with adding a Docker integration test workflow. Furthermore, the user updated the installers with the postgres setup. These contributions suggest a strong emphasis on automating builds, tests, and deployment processes.
modelinglegenddata-modelinggoldman-sachs
finos/legend-engine
Jul 2021 - Jan 2023
Legend Engine module
Role in this project:Backend Developer & DevOps Engineer
Backend Developer & DevOps EngineerContributions:1 release, 347 reviews, 57 commits in 1 year 6 months
Contributions summary:Ephrim's commits demonstrate a focus on backend development, particularly involving the integration of BigQuery support and refactoring existing identity and authentication frameworks. They also contributed to the codebase by removing hardcoded Windows temp paths and updating identity APIs. Further commits show a deep understanding of the system's internal workings as evidenced by updating the connection pool state management and refactoring SQL execution configuration, while integrating and testing connections with Snowflake, Databricks, and Redshift.
modelinglegend
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