Rakshitha J Email & Phone Number

United States

Boston, Massachusetts, United States

At RxSense, my main job is to make sure healthcare data is managed effectively and to improve how we analyze it. I assess our current AWS infrastructure to find ways to make it better. I work on making our data processing faster so we can keep up with the needs of healthcare. Using tools like Apache Beam and PySpark, I organize and transform data to create a central place for healthcare information. Following rules like HIPAA, which protect patient privacy, is very important in my work. I also focus on automating tasks and keeping our data safe using tools like AWS Data Pipeline and AWS IAM. Testing our solutions and making sure they work correctly is a big part of my job too. Working closely with others involved, I'm always looking for ways to make managing healthcare data easier and more effective-Led planning sessions to align project goals with healthcare regulations, ensuring compliance with HIPAA standards.- Collaborated with stakeholders to define project objectives and success criteria, ensuring clear communication and alignment.- Conducted a thorough assessment of AWS RDS infrastructure, identifying areas for improvement.- Enhanced data pipelines and introduced real-time processing to meet dynamic healthcare data needs.- Designed and implemented efficient data pipelines using Apache Beam, focusing on streamlining ETL processes.- Utilized dbt for seamless data transformations and modeling, contributing to a unified healthcare data repository.- Strategically planned the integration of Amazon MSK to strengthen real-time data streaming capabilities.

Deerfield, Illinois, United States

- Conducted a comprehensive evaluation of existing infrastructure to identify areas for enhancement and optimization.- Acknowledged the need to streamline data pipelines and introduce real-time processing capabilities to meet dynamic healthcare data demands.- Developed and implemented streamlined data pipelines using Apache Beam, focusing on refining ETL processes.- Devised strategic blueprints for integrating Amazon MSK to fortify real-time data processing, enhancing interaction with PySpark for advanced analytics.- Employed SQL queries and stored procedures for in-depth data analysis and manipulation within relational databases.- Utilized PySpark for executing intricate data processing tasks and conducting advanced analytics on extensive datasets, ensuring seamless integration with AWS S3 for cost-effective storage and archival.- Vigilantly monitored project progression to maintain alignment with schedules and successfully achieve milestones, utilizing AWS CloudTrail for auditing and logging of API activities.

Collaborated with stakeholders to understand existing ETL infrastructure and business requirements thoroughly.- Evaluated ETL solutions like Informatica, Azure Data Factory, and Talend to determine suitability based on capabilities.- Designed and implemented a comprehensive system architecture incorporating Informatica, Azure services, and Talend for seamless ETL workflows.- Deployed Azure Event Hubs and Azure Data Lake Analytics for real-time data ingestion and detailed dataset analysis.- Organized ETL workflows using Apache Airflow and optimized container orchestration with Kubernetes for efficient resource management.

Pune, Maharashtra, India

- Implemented Apache Airflow to manage and monitor data workflows for smooth processing.- Ensured seamless deployment of analytics solutions using Python, SQL, and PySpark.- Conducted rigorous testing and validation to guarantee the reliability and accuracy of analytics results.- Collaborated closely with stakeholders to review progress and address any concerns during deployment.

Chennai, Tamil Nadu, India

- Assessed Oracle databases to pinpoint areas for optimization and defined project objectives for enhancement.- Developed strategies for enhancing performance, reliability, and maintenance of Oracle databases.- Implemented complex SQL queries and PL/SQL scripts for effective data extraction and analysis.- Utilized Informatica PowerCenter for seamless data integration and Apache Kafka for real-time data streaming.- Automated processes with Jenkins and deployed applications using Docker for consistent deployment.