
Patrick Cockwell
Verified Expert in Engineering
Full-stack Developer
Chiang Mai, Thailand
Toptal member since April 6, 2020
Patrick is a full-stack developer specializing in data engineering, ETL processes, database design and management, analytics, and infrastructure. He's worked with Apache Airflow, Kubernetes and is familiar with GCP and AWS platforms. Patrick has great attention to detail and prefers designing systems for automation and extensibility. Patrick is a strong developer with knowledge of Python, Ruby, PHP, JavaScript, HTML, CSS, SQL, and Terraform.
Portfolio
Experience
- Python - 6 years
- PostgreSQL - 5 years
- Terraform - 4 years
- Data Engineering - 3 years
- Ruby on Rails (RoR) - 2 years
- Google Cloud Platform (GCP) - 2 years
- Amazon Web Services (AWS) - 2 years
- Kubernetes - 2 years
Availability
Preferred Environment
Amazon Web Services (AWS), Python, Terraform, Google Cloud Platform (GCP), PostgreSQL, Apache Airflow, Ruby on Rails (RoR), Ruby, GitHub, Git, Slack, Sublime Text, MacOS
The most amazing...
...thing I've developed is a custom database schema used to normalize varying customer datasets into a common data model for use with data science applications.
Work Experience
Developer
OpenCraft
- Developed Terraform modules to encapsulate infrastructure definitions and allow rapid infrastructure deployment for new clients.
- Contributed to React and Redux web applications for the edX front-end projects, and Python and Django application logic for the core edX platform (and other) projects.
- Assisted in implementing multiple monitoring and reporting mechanisms for OpenCraft systems to help track and improve client conversions and resource management.
Data and DevOps Engineer
Flyr Labs, Inc.
- Redesigned and rebuilt the Flyr infrastructure on GCP using Terraform to provide permissions-based security, data and application isolation, and ease of deployment.
- Built an ETL platform from scratch using Python, Apache Airflow, and Kubernetes that runs dozens of jobs and transfers hundreds of GBs of data per day in a performant and data idempotent manner.
- Assisted in the design, development, and implementation of a custom data model to transform client data into a uniform format to be used by internal data science applications.
Software/DevOps Developer
Agari Data, Inc.
- Performed extensive IP space research to ensure that the nternal data stores were correct.
- Guided the design, development, and execution of a disaster recovery plan for the AWS infrastructure and ensure stability, redundancy, and recoverability of data, infrastructure, and applications.
- Compared logging solutions for long-term log storage, parses, and searches.
- Developed multiple web interfaces and supported an application for an email cybersecurity tool.
Software Engineer
Breeze
- Developed multiple integrations with complex external APIs to gather data ranging from credit reports to vehicle locations and mileage.
- Managed and enhanced the entirety of the data and analytics infrastructure.
- Built tools to improve the accuracy and reliability of reports to external interests and parties.
Experience
Airflow ETL Platform and Canonical Data Model
Each client has unique internal representations of the data, which are transmitted to the organization data stores on varying schedules and frequencies using an Airflow ETL platform. The data is then processed and stored into the canonical data model (CDM) such that the machine learning (ML) models generated by the data science team can operate on the data.
This CDM is used across all clients and requires data idempotent and custom transformations for each client.
Complex Infrastructure Management System with Terraform
Disaster Recovery Plan
This involved data replication across AWS availability zones (AZ), and changes to infrastructure to shift the load across multiple AZs. Once the infrastructure changes and data replication were made, a full availability zone failure was simulated by terminating and stopping all resources in a single AZ. We provably showed that the system remained resilient, and no data loss occurred.
Orion Analytics Platform
https://github.com/gree/OrionThis tool enabled the user to select multiple types of graphing capabilities including data breakdowns across metric subcategories and period lookbacks (e.g., week over week comparison).
Users were authenticated using one of the multiple methods (OAuth being the primary means). They could also create and save dashboards for use across the company, add external links, and drill down into an individual graph or dataset.
This tool was used to help diagnose and notify Apple of App Store payments outage in June 2012 prior to their knowledge outage. The Orion Analytics Platform was developed at Funzio, which was purchased by Gree International in May 2012, and was open sourced in Aug/Sept 2012.
Education
Bachelor's Degree in Software Engineering
University of Waterloo - Waterloo, Ontario, Canada
Skills
Libraries/APIs
jQuery, React, Amazon Rekognition, REST APIs
Tools
GitHub, JSX, Terraform, Apache Airflow, Git, Sublime Text, Slack, MongoDB Atlas, Logging, Google Kubernetes Engine (GKE), AWS IAM
Languages
Python, SQL, HTML, CSS, Ruby, JavaScript, TypeScript, PHP
Paradigms
DevOps, ETL
Platforms
Google Cloud Platform (GCP), Amazon Web Services (AWS), Kubernetes, Docker, MacOS, Amazon Alexa, AWS Lambda, Heroku
Storage
PostgreSQL, JSON, Amazon S3 (AWS S3), Google Cloud Storage, Datadog, MongoDB, Database Administration (DBA), MySQL, Redis
Frameworks
Django, Django REST Framework, Ruby on Rails (RoR), Redux
Other
Data Engineering, Cloud Architecture, Google BigQuery, CSV, Automation Tools, Consul, Open Source, Disaster Recovery Plans (DRP), Analytics, APIs, Amazon API Gateway, Amazon Route 53, Google Pub/Sub
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