Skills
Backend Data Systems
- API design: Developing RESTful APIs, lightweight query languages, real-time streaming over WebSockets
- ETL and archiving: Batch and streaming ingestion, selecting and optimizing databases for different access patterns, custom scripts to tame unruly datasets
- Tools: Python (Django, Flask, NumPy), Node.JS, Postgres + PostGIS, AWS Redshift
User Interface Engineering
- Single Page Applications: Creating browser applications with routing, text and map-based search, and OAuth login
- Data Visualization: Combining charts, maps, and text to provide interactive context about a dataset
- Tools: JavaScript (ES6), Ember, React, Sass, Leaflet, HighCharts
Cloud Infrastructure
- Continuous Delivery: Reliable feature delivery with build pipelines that run test suites and deploy updates across production servers
- Tools: AWS (EC2, Elastic Beanstalk, Lambda, Kinesis, and many more), Ansible, NGINX, Unix scripting
Experience & Education
Software Engineer | Sourceress | October 2017 - Present
Software Engineer | Argonne National Lab - Urban Center for Computation and Data | Sep 2015 - June 2017
Software Engineering Co-op | Rockwell Automation | Jan 2014 - Aug 2014
B.S. Computer Science | University of Pittsburgh | August 2011 - April 2015
Selected Projects
Sourceress
Artificial intelligence recruiter that uses tailor-made machine learning models to find great engineering candidates.
Engineer: October 2017 - Present
- Improved core infrastructure for combining human labels and machine learning-generated predictions to generate ratings on candidates.
- Co-wrote new search system that let contractors to perform complex searches over hundreds of thousands of candidate profiles in a few seconds (compared to old system which took minutes).
- Worked closely with business operations team to provide better metrics for contractor performance and develop features to improve contractor productivity.
Plenario (@Argonne National Lab)
Web application that enables space and time-based discovery of open data. Provides API for querying across datasets.
Lead Engineer: September 2015 - June 2017
- Took from prototype to production-ready application depended on by academic users and the City of Chicago's opengrid.io.
- Designed and implemented real-time data pipeline using AWS Kinesis, Lambda, and Redshift to ingest and stream data from the Array of Things sensor network.
- Built up engineering team by recruiting three new engineers and mentoring junior developers and interns.
- Improved response time of most important family of queries by a multiple of 10 by redesigning the database and optimizing client code.
- Rewrote ingestion process to improve reliability and scale with demand.
- Increased speed of feature delivery by migrating from hand-rolled EC2 instances with manual deployments to push-to-deploy with Elastic Beanstalk and Travis CI.
- Tools: Python (Flask), JavaScript (Ember for frontend, Node for streaming pipeline)
Community
Talks
- JavaScript for Data Analysts, March 2017
- Chapin Hall Center for Children
- Open Data, Open Government, Feb 2017
- PyData Chicago Meetup
- Databases for Smart Cities, Nov & Dec 2016
- Guest lecture at University of Chicago and DePaul University Masters database courses
- SQLAlchemy: Beyond ORM, Dec 2015
- Chicago Python Meetup
Volunteering
- PyData Chicago Meetup
- Build Night Host: Feb 2016 - Dec 2016
- Chicago Python Meetup
- Web Development Mentor: Spring 2016
Panels
- Open Data Roundtable on Public-Private Collaboration, June 2016
- White House Office of Science and Technology Policy
- International Symposium on Urban Living Labs, February 2016
- UK Collabatorium for Research on Infrastructure and Cities
