Chris Eichelberger
Chief Data Officer
Charlottesville, Virginia, United States
Summary
🤩
Rockstar🎓
Top SchoolChris Eichelberger is a seasoned data and engineering leader with over three decades of experience building data pipelines, analytics platforms, and high-performing teams, and he currently serves as Chief Data Officer at Castle Hill Gaming. He blends hands-on engineering—contributing to open-source geospatial tooling like GeoMesa—with strategic leadership from prior roles as Senior Director of Engineering and Director of Software Engineering. Chris’s expertise spans machine learning, distributed systems, predictive modeling, and visualization, with a track record of optimizing core data-processing components for performance and correctness. Known for a people-first management style, he emphasizes respect, transparency, and feedback to translate complex analytics into business value. His career bridges academia and industry, from directing a university software lab to embedding ML in vertical applications for finance and healthcare. An unconventional detail: he pairs deep technical work with a liberal arts background, reflecting a problem-solving approach that values narrative and context as much as algorithms.
14 years of coding experience
26 years of employment as a software developer
ABD computer science, ABD computer science at University of North Carolina at CharlotteB.A. liberal arts and sciences, B.A. liberal arts and sciences at Virginia TechM.S. computer science, M.S. computer science at University of Florida
Github Skills (11)
javas10
spatial10
geo10
query-optimization10
geospatial10
accumulo10
java10
spatial-data10
scala10
testing9
api-design8
Programming languages (4)
Github contributions (5)
locationtech/geomesa
Oct 2013 - Nov 2018
GeoMesa is a suite of tools for working with big geo-spatial data in a distributed fashion.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:39 commits, 61 PRs, 71 pushes in 5 years 1 month
Contributions summary:Chris primarily contributed to the `geomesa-core` and `geomesa-utils` modules, implementing features related to geospatial data handling. Their work included optimizing the geohash substring generation, enhancing the filter-to-accumulo process for AND/OR queries, and fixing issues related to feature IDs and date handling. Furthermore, the user refactored the CartesianProductIterator for performance optimization. These changes indicate a focus on improving core functionality and data processing efficiency within the GeoMesa framework.
geomesageo-spatialgeospatialkuduaccumulo
geomesa/geomesa-quickstart
May 2014 - May 2015
Contributions:4 commits, 1 PR, 2 pushes in 11 months
geomesajavascriptgis
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