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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.

• Programming
• Python
• SQL
• Docker
• Bash Scripting
• Github Actions
• Terraform

• Data Engineering
• Snowflake
• Airflow
• Spark
• Postgres
• SQL Server
• Database Design

• AWS Services
• SageMaker
• ECR/ECS
• Lambda
• RDS
• Glue
• EMR

• Analytics & Monitoring
• Streamlit
• Jupyter
• Plotly
• Model Monitoring
• Inference Workflow Design