Jayanthi Chandrasekar Email & Phone Number

Virginia, United States

1.Designed and deployed ETL pipelines using Azure Data Factory, integrating veterans' healthcare data from multiple sources into Azure Data Lakes and warehouses.2. Automated data ingestion processes with custom triggers and schedules, ensuring accurate, real-time updates.3. Leveraged Azure Databricks and Spark clusters for distributed computing, enabling real-time analytics, machine learning model training, and predictive insights.4. Developed interactive Power BI dashboards visualizing healthcare KPIs, helping stakeholders make informed decisions on patient outcomes and resource utilization.5. Built and optimized SQL-based data models, relational databases, and stored procedures for efficient data storage and processing.6. Implemented advanced analytics and machine learning workflows in Python, integrated into Azure platforms for seamless automation.7. Managed code repositories, branches, and collaborative workflows via GitHub, ensuring smooth deployment processes.

Texas, United States

1. Built and optimized large-scale data pipelines using Azure Synapse Analytics, ensuring efficient ingestion, transformation, and storage of network data.2. Leveraged Apache Spark for distributed computing, enabling high-performance analytics on diverse datasets related to network performance and customer usage patterns.3. Developed interactive Power BI visualizations, providing actionable insights into network performance, customer behavior, and usage trends.4. Utilized SQL and Python to query, manipulate, and automate data processes, ensuring accuracy and efficiency in data workflows.5. Collaborated with cross-functional teams to design scalable data solutions aligned with business requirements, enhancing AT&T’s network operations.6. Managed database tasks in SQL Server Management Studio (SSMS), optimizing schema design and performance tuning for efficient data retrieval and storage.7. Employed Azure Data Explorer for real-time data analysis and proactive monitoring of network performance.

Illinois, United States

1. Automated infrastructure provisioning using AWS CloudFormation, reducing deployment time and improving scalability.2. Optimized system responsiveness through serverless architectures with AWS Lambda for critical applications.3. Integrated Snowflake with AWS services, enabling seamless data storage, analytics, and reporting for large-scale datasets.4. Delivered real-time insights with Amazon Quicksight, empowering stakeholders to make data-driven decisions.5. Enhanced data retrieval and analysis using Amazon Athena and complex SQL queries.Streamlined ETL processes with AWS Glue, ensuring data integrity and reliability across systems.6. Accelerated software delivery cycles by configuring Jenkins pipelines for CI/CD.7. Automated manual tasks with Python scripting, boosting productivity and efficiency.8. Architected cost-effective, scalable AWS solutions, ensuring high availability for mission-critical applications.9. Integrated AWS services into cohesive, end-to-end solutions aligned with business objectives.10. Demonstrated strong problem-solving skills, fostering innovation and continuous improvement across projects.

Atlanta, United States

1. Developed and optimized PySpark applications in Hortonworks HDP 2 ecosystem, leveraging Apache Spark for scalable, distributed data processing.2. Implemented complex ETL pipelines to enhance data quality and consistency in healthcare datasets using PySpark, HBase, and Hive.3. Utilized Sqoop for seamless data transfer between Hadoop and relational databases, improving external data ingestion workflows.4. Orchestrated job scheduling and monitoring with Oozie, ensuring timely execution of data processing pipelines.5. Collaborated with cross-functional teams to integrate PySpark applications with MongoDB, enabling efficient data access for healthcare analytics.6. Contributed to project planning, design, and deployment, driving continuous improvements in system capabilities and processes.

Tamil Nadu, India

1. Proficiently utilized DataMarts to extract, transform, and load (ETL) data from diverse sources, ensuring data accuracy and integrity for downstream analysis.2. Leveraged Microsoft SQL Server Management Studio (SSMS) for database administration tasks, including query optimization, performance tuning, and troubleshooting data issues.3. Developed interactive and visually appealing reports and dashboards using Microsoft SQL Server Reporting Services (SSRS), facilitating data-driven decision-making for stakeholders.4. Designed and implemented complex ETL workflows using SQL Server Integration Services (SSIS), automating data processing tasks and improving operational efficiency.5. Utilized PL/SQL for data manipulation and analysis, writing efficient queries, stored procedures, and functions to extract insights from large datasets.6. Collaborated with business stakeholders to understand requirements and translated them into actionable insights using Python and Tableau, driving strategic decision-making and business growth.