Experience
Lead Data Engineer (MLOps) at Zelis
August 2021 – Present
- Lead MLOps and data engineering initiatives to operationalize AI/ML solutions using Snowflake, AWS, and Airflow.
- Designed and deployed end-to-end ML pipelines leveraging AWS SageMaker, Docker, and Airflow.
- Developed model monitoring dashboards using Streamlit and integrated metrics collection workflows.
- Automated AWS infrastructure with Terraform, enabling scalable and reproducible deployments.
- Built and containerized inference workflows, managing deployments via ECR, ECS, and Lambda.
- Collaborated with data scientists to productionize ML models and deploy scalable, maintainable systems.
- Designed data pipelines integrating Snowflake and orchestrated with Apache Airflow.
- Developed Spark pipelines to support large-scale data processing.
Sr. Data Analyst at CH Robinson
January 2014 – August 2021
- Conducted exploratory data analysis in Jupyter to derive actionable insights.
- Built interactive dashboards with Plotly, Streamlit, Power BI, and R Shiny.
- Optimized SQL queries across SQL Server, Postgres, and Hive databases.
- Developed Python-based ETL and reporting solutions.
- Ensured data integrity through integration of disparate data sources.
- Worked cross-functionally to translate business needs into data-driven outcomes.
Skills
Programming
Python
SQL
Docker
Bash
GitHub Actions
Terraform
Data Engineering
Snowflake
Airflow
Spark
Postgres
SQL Server
Database Design
AWS Services
SageMaker
ECR / ECS
Lambda
RDS
Glue
EMR
Analytics & MLOps
Streamlit
Jupyter
Plotly
Model Monitoring
Inference Workflows
Education
University of Massachusetts Lowell
Information Technology – B.S.
- Programming and relational databases focused coursework