Chris Goddard
Lead Software Engineer at Center for Agentic AI Research
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolChris Goddard is a Lead Software Engineer and data-savvy technology leader with 13 years of experience building cloud-native data platforms and analytics for political and nonprofit organizations. Based in Seattle and originally from New Zealand, he blends hands-on engineering with product and consulting experience through his firm Good Kiwi LLC and current role at the Center for Agentic AI Research. He architected mission-critical pipelines at the DCCC—1200+ dbt models on GCP/BigQuery with Prefect and Kubernetes—delivering voter targets and hourly dashboards under strict SLAs. Comfortable at the intersection of engineering and strategy, he's led cross-functional analytics teams for global clients and streamlined integrations with systems like Votebuilder and Mobilize. An obsessive editor of technical docs and educational resources (including contributions to Quantopian’s public lectures), he cares as much about clarity and reproducibility as about performance and scale. Known for speaking “nerd and suit” fluently, he focuses on pragmatic AI and data products that advance Democratic campaigns and civic causes.
13 years of coding experience
7 years of employment as a software developer
Marketing, Marketing at UW Foster School of BusinessBCom Marketing, BCom Marketing at University of Canterbury
English
Stackoverflow
579reputation
34kreached
3answers
4questions
Github Skills (12)
latex10
documentation10
typehinting6
google-cloud-storage6
google-compute-engine6
docker6
php6
google-cloud-platform6
python-typing6
python6
google-api-python-client6
google-analytics6
Programming languages (18)
Github contributions (5)
quantopian/research_public
Jun 2017 - Aug 2017
Quantitative research and educational materials
Role in this project:
Technical Writer
Technical WriterContributions:27 commits in 2 months
Contributions summary:Chris's commits primarily focus on updating links and correcting latex typos within the Quantopian lecture series. They updated links in multiple lectures, including those on NumPy, Random Variables, Hypothesis Testing, and Spearman Rank Correlation, ensuring the accuracy and accessibility of the educational materials. Additionally, they corrected latex typos in the ARCH GARCH GMM lecture. This indicates a focus on maintaining the quality and integrity of the documentation.
quantitative-researchsciencebrain-computer-interfacedata-sciencescientific-computing
chrisgoddard/singer-discover
Feb 2019 - Nov 2019
A simple utility to edit Singer-spec schemas in the command line.
Contributions:16 commits, 2 PRs, 9 pushes in 8 months
command-line-toolsubcommandssingercommandline-toolspec
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