Jackson J. Gilman

Input • Ideation • Analytical • Intellection • Achiever

I am a software and data engineer with a passion for test automation, DevOps and GIS. Proud “Pythonista” since 2006.

This resume is maintained in my GitHub and is updated frequently

Technical Skills

✏️ Highly experienced in Python with past development experience in JavaScript. Proficient in Bash scripting and Makefiles to accelerate developer on-boarding.
🧠 Very knowledgeable using PostgreSQL, Redshift, Kafka, with experience in MySQL, MemSQL, and Microsoft SQL Server, Elasticsearch and Neo4J.
☁️ Very experienced working with a variety of AWS services including (but not limited to) S3, SQS, SNS, EC2, Step Functions, EventBridge, Lambda and Transfer Family
🏗️ Regularly work with popular DevOps tools such as ArgoCD, Kubernetes, Terraform, Hashicorp Vault, Concourse, Jenkins
🧪 Versed in TDD/BDD practices. Regularly use py.test, but familiar with other test tools.
📚 Libraries and frameworks I currently work in: Apache Airflow, SQLAlchemy, FastAPI

Technical Lead @ Outcomes: Jul, 2023 — Current

Transitioned with current team and role through acquisition.

Lead the migration of applications from a proprietary PaaS to Kubernetes. This involved containerizing existing applications that used proprietary “build packs”
Prototyped and released a managed file transfer solution on top of AWS Transfer Family with automated antivirus scanning and custom identity-provisioning.
Since this project was a collaboration with core infrastructure and SecOps teams, I authored Gherkin feature files backed with a suite of tests using behave to clearly communicate functionality of the system. Other collaborators that were unfamiliar with Python were still able to run these tests without any manual configuration on their end (i.e. make test)

Technical Lead @ Cardinal Health (Fuse): Sep, 2019 — Jul, 2023

I lead a fully-remote team of engineers tasked with solving a variety of data challenges. Some of my accomplishments of note:

Forging designs for moving away from batch processes toward an event-based architecture, leveraging Kafka. Using third-party CDC tools to assist with migrating to said architecture.
Driving forward-engineering efforts to build better monitoring and alerting solutions for day-to-day operations.
Migrating an existing batch system written in Python (100k+ LoC) to a solution built on top of Apache Airflow in order to make it easier to scale for growth and improve operational visibility. Introduced build orchestration for the existing project and added automated test tooling which greatly reduced risk during refactoring.
Set up Ansible playbooks and trained staff on managing the configuration of our Airflow installation. Also put together a streamlined way of executing playbooks via Concourse due to organizational CI/CD requirements.
Using Sphinx, configured the build for our main project to produce literate, code-driven documentation which was not only useful for the engineers on the team, but also to our business partners. They regularly refer to it when finding answers to questions about how we ingest data from our many external sources.
Regularly coordinated with other teams who use our data. Drove a practice for our team to supply thorough documentation of our schema in Alation.
Developed a reputation as a “go-to” for Python questions in my organization.
Primarily responsible for designing project CI/CD pipelines for Concourse.

Software Engineer @ Cardinal Health (Fuse): Jan, 2014 — Sep, 2019

Initially hired as a JavaScript application developer, I assumed a more DevOps-centric role on my team.

Presented with an existing ETL pipeline (Python), my team was tasked with a large Python code base into a onto an Apache Airflow stack deployed to PCF.
Used Packer to generate a common development environment so Windows and MacOS engineers could work side-by-side. Built concourse CI/CD pipeline. The team is able to continue development uninterrupted during refactor, and is still able to maintain the existing stack all while the modernization effort.
Actively involved with org-wide initiative to define current and new infrastructure using Terraform. As an early adopter, my team was able to take advantage of the self-service nature of IaC while improving transparency of our project’s AWS resource usage (cost).
Frequent contributor to our internal Chef repository to unblock my team due to configuration management needs.
Facing a potentially weeks-long OCR project, designed a workflow with Celery that was deployed to scale on an Apache Mesos platform.
Introduced test automation to existing data ingest pipeline built around Kafka and MemSQL. Developed additional apps with Kafka Streams, deployed to PCF.
Deployed a VPC in AWS with Terraform including EC2 instances for Kafka and MemSQL clusters. Authored an internal Chef cookbook to provision MemSQL installation.

Sr. GIS Developer @ City of Memphis (contractor): Aug, 2013 — Jan, 2014

Sr. GIS Developer @ FedEx (contractor): Nov, 2012 — Aug, 2013

Extended ArcGIS JavaScript API to provide custom interactive map layer when out-of-the-box features were not available.
Designed Node.js test harness/proxy and basic unit test suite (Karma/Jasmine) to decouple front-end development from backend dependency. This allowed developers to build the application without the requirement of running local JEE web server, drastically improving efficiency by reducing test feedback cycle time.

Sr. GIS Developer @ BNSF Railway (contractor) May, 2011 — Nov, 2012

Built ETL / Geoprocessing workflows (Python) to prepare mapping data for use in ArcGIS Schematics project. This included the use of spatial SQL queries, linear referencing and topologies.
Lead on developing and supporting multiple JavaScript web mapping applications serving operations and engineering personnel. One application built using Google Maps API.
Managed aspects of ArcSDE geodatabase running against DB2 Spatial Extender.

GIS Programmer and Cartographer @ University of Memphis: Sep, 2007 — Apr, 2011

Authored maps representing a variety of data elements, including parcel, real estate, crime, public resources, transportation, education and census demographics.
Designed automation around statistical reporting, mostly around foreclosure activity during the 2008 housing crisis.
Built web scrapers (Python) to crawl the public record.
Tailored composite address locators to provide highly accurate geocoding output.