Jul 2021 – Aug 2024 · 3 yrs 1 mo · United States · Hybrid

• Designed and implemented scalable data architectures using AWS services, ensuring robust data storage, processing, and retrieval capabilities.
• Developed and optimized ETL processes within the AWS environment to ensure data integrity, performance, and seamless integration with downstream analytics platforms.
• Integrated Power BI with Snowflake and Tableau for enhanced reporting capabilities, enabling advanced data visualizations and cross-platform analytics.
• Leveraged cloud-native tools on AWS, Azure, and GCP to design and manage scalable databases, such as Amazon RDS, Azure SQL Database, and Google Cloud Spanner, optimizing performance, scalability, and cost-efficiency.
• Implemented AI-driven analytics within Power BI, utilizing machine learning models to provide predictive insights and enhance data-driven decision-making.
• Collaborated with healthcare professionals to identify key metrics and created AI-enhanced dashboards that support improved decision-making in clinical and operational settings.
• Developed automated data quality frameworks using AWS Glue and Amazon Athena, ensuring the accuracy, completeness, and consistency of healthcare data.
• Monitored and optimized cloud resources on AWS and GCP, ensuring efficient operation and cost management across data processing workflows.
• Implemented CI/CD pipelines using Jenkins, CircleCI, and GitLab CI**, automating deployment processes and ensuring data quality and integrity across all stages.
• Deployed and managed Docker containers within cloud environments, implementing security best practices such as image scanning and vulnerability management to protect sensitive data.
• Selected appropriate cloud services for data storage, processing, and analytics, ensuring alignment with organizational needs and optimizing for performance and cost.

Oct 2019 – Jun 2021 · 1 yr 8 mos · United States · Hybrid

• Led the migration of on-premises data infrastructure to AWS, achieving significant cost savings and improved scalability, while ensuring seamless integration with existing systems.
• Monitored and optimized Snowflake performance, implementing cost-saving strategies and enhancing query efficiency to meet high-performance requirements.
• Collaborated with data scientists and analysts to develop and deploy machine learning pipelines on AWS Glue and SageMaker, facilitating advanced predictive analytics.
• Provided training and knowledge-sharing sessions on Apache Airflow, promoting a culture of reliability and efficiency in data pipeline management across cross-functional teams.
• Conducted data analysis to uncover trends and patterns in patient outcomes, resource utilization, and clinical performance, supporting evidence-based decision-making in healthcare projects.
• Optimized CI/CD pipeline performance for faster deployment cycles and enhanced reliability, utilizing advanced automation tools and best practices.
• Ensured compliance with FDA regulations during clinical trials, including secure data collection, reporting, and monitoring, meeting stringent regulatory standards.
• Developed and delivered visualizations and reports using Databricks notebooks, effectively communicating data-driven insights to stakeholders.
• Implemented scalable data pipelines using Azure Databricks, enabling efficient data movement, transformation, and real-time analytics.
• Leveraged Apex callouts for secure and efficient interactions with external APIs, ensuring smooth data exchange and integration with third-party services.
• Implemented experiment tracking for PyTorch models using MLflow and Weights & Biases, ensuring transparency, reproducibility, and streamlined model development processes.

Aug 2015 – Sep 2019 · 4 yrs 1 mo · United States · On-site

• Data Architect / Data Modeler
• August 2015- September 2019
• Employer – NPV Staffing LLC
• Clients: United Health Group (OPTUM)
• Worked on tables for Medicare and Medicaid data models, building a dimensional model connecting Individual and Members subject areas.
• Converted data models into logical and physical models using Power Designer and ER Studio.
• Configured and maintained communication networks for SCADA systems, including Ethernet, Modbus, OPC, and other industrial protocols, ensuring reliable and secure data transmission.
• Collaborated with healthcare stakeholders to gather requirements and translate them into scalable data architecture solutions.
• Establishing protocols for responding to and reporting data breaches involving PHI as required by HIPAA.
• Monitored and tuned MySQL database performance using tools like MySQL Workbench and Percona Toolkit.
• Conducted design walkthroughs with business teams to ensure requirements and standards were met.
• Implemented ETL processes with Informatica to extract historical data.
• Designed integration solutions using ESB and other orchestration tools for seamless data flow between applications.
• Developing and enforcing data retention policies in line with HIPAA regulations to ensure the proper handling and disposal of PHI.
• Contributed to migrating on-premises data infrastructure to AWS, resulting in significant cost savings.
• Developed real-time data processing applications using Kafka Streams and Kafka Connect.
• Ensured systems support patient rights under HIPAA, including access to their own PHI and requesting corrections to their records.
• Applied normalization and denormalization techniques in relational and dimensional environments.
• Conducted complex data analysis and created visualizations using Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn to derive actionable business insights.
• Implemented data pipelines for data movement and transformation using Azure Databricks.