Data & Cloud Engineering
Senior software and data engineer with 10+ years of experience building scalable data platforms and cloud infrastructure. Specializing in AWS, GCP, data pipelines, and machine learning systems.
About
I architect and implement enterprise-grade data solutions across diverse industries including eCommerce, financial services, agriculture, and technology. My work focuses on transforming complex data challenges into production-ready systems that scale.
What I Do
- Build data pipelines and ETL/ELT workflows
- Design cloud-native architectures (AWS, GCP)
- Implement data lakes and warehouses
- Deploy machine learning platforms
- Optimize infrastructure and reduce costs
Experience
Currently working with clients through Plenert Macdonald Software Services on:
- Product data ingestion pipelines (Palantir Foundry, PySpark)
- Financial data platforms (GCP, Kubernetes)
- CRM/ERP data modeling (DBT, SQL)
- ML training pipelines and IoT analytics
Previously: Principal Developer at Shell Hydrogen, Data Engineer at Amazon (InfoSec, PrimeNow), Machine Learning Engineer at Webroot and KnuEdge.
Technologies
Cloud: AWS (Redshift, S3, Glue, EMR, Lambda, Kinesis), GCP (Cloud Storage, Cloud Run, Spanner, Kubeflow)
Data: Palantir Foundry, DBT, PySpark, Polars, Pandas, SQL
ML: Scikit-learn, TensorFlow, MXNet
Infrastructure: Kubernetes, Docker, CI/CD
Education
B.S. Physics (minor Computer Engineering), UC San Diego
Contact
Email: software@apmac.us
GitHub: github.com/aodhan-domhnaill