Daniel Parker

Software Engineer at Causal

Austin, Texas, United States
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Summary

👤
Senior
Daniel Parker is a seasoned software engineer with 25 years of development experience and 11 years in senior engineering roles, currently building web products at Causal from Austin, Texas. He has led cross-functional teams and architected reusable platforms—most recently designing a GraphQL cross-product solution and a search platform that served multiple products. Daniel combines deep frontend expertise (notably as engineering lead for Evernote’s multi-client note editor) with pragmatic full-stack problem solving, including building a lightweight Apache Thrift JS client and serialization tools for PDF annotations. An author of O’Reilly’s JavaScript with Promises, he is also an active open-source contributor who improved ProseMirror’s table module by refining table selection semantics and streamlining its implementation. Known for resolving tricky concurrency and cross-system bugs, he focuses on maintainable, testable architectures and enjoys crafting software with great teams.
code10 years of coding experience
job26 years of employment as a software developer
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Github Skills (3)

javascript10
prosemirror10
front-end-development9

Programming languages (3)

TypeScriptJavaScriptHTML

Github contributions (5)

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Table module for ProseMirror
Role in this project:
userFull-stack Developer
Contributions:5 commits, 2 PRs, 4 comments in 15 days
Contributions summary:Daniel contributed to the development of the table module for ProseMirror. Their work involved exposing and implementing useful table functions, such as adding and removing columns/rows. The user also addressed how table selections are treated by treating node selections of table cells like cell selections. Furthermore, the user streamlined code by removing unnecessary imports and merging code changes.
prosemirror
Code examples from "JavaScript with Promises: Managing Asynchronous Code"
Contributions:1 review, 4 commits, 1 PR in 1 month
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Daniel Parker - Software Engineer at Causal