9+

years of experience

2 yrs

Cloud Engineer @ CVS Health

5 yrs

tech lead at Infosys

M.S.

Data Science — Ball State

The stack I live in

These are the GCP services I work with regularly — not a checkbox list, but tools I've used to solve real problems.

BigQuery

Data Warehouse

Dataflow

Stream & Batch Processing

Pub/Sub

Messaging & Streaming

Cloud Composer

Workflow Orchestration

Cloud Storage

Object Storage

Dataproc

Spark & Hadoop

Cloud Functions

Serverless Compute

Cloud Run

Containerized Workloads

Looker / Looker Studio

BI & Visualization

Vertex AI

ML Platform

IAM & Security

Access & Identity

Terraform (GCP)

Infrastructure as Code

Google Kubernetes Engine

Container Orchestration


Across the stack

Data Engineering

Pipeline design & architecture ETL / ELT Batch processing Data modeling Data quality & validation Workflow orchestration On-prem to cloud migration Healthcare data

Languages & Tools

Python SQL Apache Airflow Apache Beam Flask Docker GitHub Actions SonarQube Tableau Bash / Shell Git C#

AI & Governance

AI Model Inventory Compliance automation AI standards enforcement Executive reporting

Practices

Tech lead Team mentorship Code review Observability & monitoring Data governance Technical documentation Unit testing CI/CD automation Technical interviews & hiring Stakeholder communication

How I work

Reliability over speed

A pipeline that processes data correctly 100% of the time is more valuable than one that processes it twice as fast with silent failures. I build observability in from the start, not as an afterthought.

Cost-conscious by default

Cloud costs compound quickly without intent. I think about query efficiency, partition strategies, and data lifecycle from the design phase — not after someone gets a billing alert.

Infrastructure as code

If it can't be reviewed, version-controlled, and reproduced, it's a liability. Terraform for infrastructure, dbt for transformations, Airflow for orchestration — all of it in source control.

Documentation that lasts

I write documentation for the next person who has to understand the system at 2am when something breaks. The goal is clarity, not coverage. One sentence that explains the why beats five that describe the what.


Certifications & Badges

47 badges earned on Credly across GCP, AI/ML, Python, data engineering, and more. View full profile ↗


Awards

CVS Health · P2P Award

Champions AI (Q2 2026)

Recognized for outstanding leadership and expertise in adopting and scaling generative AI tools (Claude Code, GitHub Copilot) within CVS Health's engineering workflows.

Claude Code GitHub Copilot AI Engineering
"Partnering with you is always a highlight, Cody. Your insights into leveraging AI, Claude Code, Copilot and maximizing its utility have been incredibly enlightening. Plus, your comprehensive understanding of CVSHealth's underlying engineering framework is a tremendous asset that consistently elevates our work." — Prarthit Mehra
CVS Health

Heart at Work Awards

Recognized multiple times for exemplifying CVS Health values across the organization — spanning safety, simplicity, cross-team collaboration, and rising to high-impact challenges.

Champion Safety & Quality Create Simplicity Join Forces Rise to the Challenge
Google Cloud

CVS Cloud Hero — Top 10

Placed in the top 10 at the CVS Cloud Hero event held at Google Cloud — competing in hands-on challenges on Vertex AI and Google Kubernetes Engine.

CVS Health

CVS AI Coder Certification

Earned the internal AI Coder credential for demonstrating proficiency in enterprise generative AI application design, prompt engineering, secure coding practices, and AI-assisted development workflows.

Generative AI Prompt Engineering Secure Coding Enterprise Standards

Resume

View my resume

Full work history, skills, education, and certifications in one place — interactive and print-friendly.

View Resume →
Let's talk

Interested in working together?

Whether it's a data engineering question, a project idea, or something you're building — I'm reachable. GitHub is the best place to find my work.