Ssr Palli Email & Phone Number

Chicago, IL, US

Richmond, Virginia, United States

• Developed scalable, high-performance ETL data pipelines to transform and ingest data from multiple sources, enhancing data accessibility and analytics capabilities by 30%.
• Automated data integration workflows for structured and unstructured data, reducing data processing time by 40%.
• Designed and implemented data governance solutions, supporting compliance with Commonwealth Data Trust standards for secure and efficient data sharing.
• Enhanced operational analytics by building data tools that provided actionable insights for customer acquisition and operational efficiency.
• Collaborated with cross-functional teams to optimize data delivery, significantly improving data integrity and processing speed.
• Integrated real-time data pipelines using Apache Kafka, reducing data latency and enhancing response times for critical business functions.

Richmond, Virginia, United States

• Built a data pipeline using Snowflake and Apache NiFi on Amazon EC2 to automate data ingestion into Amazon S3, reducing manual work by 40% and streamlining the ETL process.
• Developed analytics tools to provide actionable insights, contributing to a 20% increase in customer acquisition efficiency.
• Streamlined internal processes by implementing AWS Glue and Apache Kafka, automating labor-intensive tasks and reducing manual interventions by 40%.
• Partnered with data science teams to design and implement tools for operational efficiency, enhancing business intelligence capabilities.
• Spearheaded data governance initiatives, creating frameworks that supported data accuracy and compliance across departments.
• Collaborated with cross-functional teams to align technical requirements with business objectives, ensuring effective data solutions.

Richmond, Virginia, United States

• Led the development of an end-to-end data pipeline using Snowflake and Apache NiFi, achieving real-time data ingestion and reducing latency by 30%.
• Designed Power BI dashboards that streamlined data accessibility for stakeholders, enhancing decision-making and data-driven insights.
• Used Azure Data Factory and AWS Redshift to create efficient ETL workflows, reducing data processing times and enhancing data warehousing efficiency.
• Implemented data governance standards, supporting secure data sharing and compliance with industry regulations.
• Automated data quality monitoring processes, minimizing data inconsistencies and ensuring accurate data for analytics.
• Engineered solutions for real-time data streaming, leveraging Apache Kafka to support high-frequency updates and improve data responsiveness.

• Developed high-quality data pipelines, integrating large and diverse datasets to support complex analytical projects for global clients.
• Implemented process improvements in ETL workflows, reducing processing times by 25% and enhancing overall data accuracy.
• Collaborated closely with data science teams to understand business requirements, enabling the development of targeted data solutions.
• Automated data ingestion workflows, decreasing manual interventions by 40% and improving data processing speed.
• Conducted data quality checks and validation processes, ensuring data integrity and reliability for downstream analysis.
• Built interactive dashboards using Tableau and Power BI, empowering stakeholders with accessible and actionable insights.

Bengaluru, Karnataka, India

• Engineered ETL processes to streamline the ingestion and transformation of financial data, reducing manual data processing times by 40%.
• Created interactive dashboards using Tableau and Power BI, empowering stakeholders with insights into financial data and performance.
• Leveraged Hadoop and Apache Spark to handle large-scale data operations, ensuring efficient processing and analysis of customer data.
• Automated data quality monitoring and reporting, improving the accuracy and consistency of data across platforms.
• Supported data governance practices, ensuring compliance with regulatory requirements and industry standards.
• Designed SQL-based data pipelines for data retrieval, enabling real-time analytics and reporting for decision-makers.