PALLAVI JINJIRAMPALLI

• · Developed and maintained robust ETL pipelines using Informatica PowerCenter and AWS Glue, facilitating daily processing of over 10 million transaction records.
• · Designed and implemented scalable ETL pipelines using Informatica PowerCenter and AWS Glue to consolidate pharmacy transaction data across 500+ stores, enhancing timeliness and accuracy of reporting.
• · Led data migration project from legacy systems to Amazon RedShift, enhancing analytical capabilities and reducing report generation time by 50%.
• · Designed and implemented real-time data warehousing solutions using Snowflake, supporting dynamic scalability and concurrent analytics.
• · Introduced Apache Airflow to manage and automate over 30 different data flows, significantly improving operational efficiency of data operations.
• · Spearheaded migration of patient data using AWS DMS, ensuring compliance with HIPAA regulations while minimizing downtime.
• · Integrated Apache Kafka with existing data systems to enable real-time data streaming and alerting for patient care notifications.
• · Wrote Python scripts to automate data cleansing processes, which improved data quality.
• · Developed Java-based tool for ETL job monitoring that reduced error detection time.

· Executed complex data transformations and integrations using Talend and SSIS across multiple client databases, ensuring data quality and consistency.

· Designed data models in SAP and Erwin for financial services, enhancing compliance reporting and audit trails for key stakeholders.

· Utilized Erwin and SAP to develop and maintain robust data models for financial reporting, which supported tax optimization projects for multinational clients.

· Deployed Databricks for scalable big data processing, enabling advanced predictive analytics and machine learning capabilities.

· Architected and optimized a multi-cloud data management solution on GCP and AWS, promoting flexibility and cost savings in data operations.

· Implemented solutions using Apache Spark and Cloudera Data Platform to analyze large-scale, diverse datasets, providing insights that drove strategic business decisions.

· Configured and maintained cloud-based data warehousing solutions using Google Cloud BigQuery, reducing data storage costs.

· Automated multiple data pipelines using Apache Airflow and Databricks, reducing manual intervention and increasing data reliability.

· Created a C# application to facilitate secure data transfers between client and internal systems.

· Implemented JavaScript-based interactive dashboards in web applications to enhance user engagement and data visualization capabilities.

· Developed a centralized data processing architecture using Apache Kafka and Apache Spark, reducing data latency from hours to minutes.

· Implemented IBM InfoSphere for comprehensive data migration, ensuring high availability and consistency across sales and distribution centers.

· Optimized data pipelines in Apache NiFi, enhancing data ingestion and extraction processes, which supported customer service analytics.

· Automated data quality checks using Microsoft Azure Data Factory, reducing manual interventions and ensuring high standards of data integrity.

· Led the development of a centralized operational data store using Microsoft SQL Server and SSIS, improving data accessibility for e-commerce logistics analysis.

· Engineered and optimized data integration flows with Talend, enhancing data synchronization across distributed systems.

· Developed and optimized data marts and implemented Tableau dashboards that provided actionable insights into customer behavior and sales trends.

· Managed the transition of data infrastructure to Microsoft Azure Synapse, achieving more scalable and cost-effective data storage solutions.

· Engineered an automated monitoring system using Shell Script to oversee data pipeline health, reducing downtime.

· Utilized Python to construct a recommendation engine which boosted sales conversions

· Spearheaded the development of an enterprise data warehouse (EDW) using Oracle Database and ODI, supporting complex financial reporting requirements.

· Engineered real-time fraud detection systems with Apache Flink and Apache Beam, decreasing fraudulent activities.

· Led the transition to cloud-based data warehousing with Amazon RedShift and Microsoft Azure Synapse, significantly improving data scalability and access.

· Implemented a strategic data model using Star and Snowflake schemas, facilitating enhanced analytical capabilities across business units.

· Constructed and maintained an EDW using Oracle Database and ODI that centralized critical financial data, supporting regulatory compliance and financial reporting.

· Utilized Apache Spark and Apache Kafka to develop a real-time fraud detection system, reducing fraudulent transactions.

· Configured and managed data pipelines in Apache NiFi, improving data flow efficiency between internal and external systems.

· Assisted in cloud migration initiatives to AWS, which included setting up AWS Glue for seamless data integration and analytics processes.

· Developed complex financial models in C++ for risk analysis, significantly enhancing portfolio management.

· Spearheaded the creation of an internal portal using HTML, CSS, and TypeScript, increasing operational efficiency.

· Managed Apache Hadoop and Cloudera Data Platform clusters for processing large-scale datasets, enabling efficient data analysis and insights.

· Developed comprehensive data pipelines using Google Cloud Dataflow and Apache Airflow, ensuring robust data governance and workflow management.

· Created and maintained NoSQL databases (MongoDB, Cassandra) to handle unstructured data, improving system performance and query response times.

· Integrated Tableau and Power BI solutions with data warehousing systems to deliver advanced visual analytics and business intelligence.

· Deployed and managed Apache Hadoop clusters, facilitating efficient processing of large-scale data sets used for predictive analytics in retail.

· Implemented Apache Flink for stream processing to provide near-real-time analytics for dynamic pricing models.

· Enhanced data lake capabilities using Amazon EMR, significantly improving data ingestion and retrieval times.

· Developed complex analytical models on Databricks, providing insights that drove high-value business strategies.

· Automated Hadoop cluster management tasks using Ruby scripts, resulting in a reduced manual workload.

· Built a Python-based data validation tool that improved data accuracy in ETL processes.

· Designed and deployed ETL processes using ODI and Apache Spark, streamlining data collection and aggregation from various sources.

· Constructed and managed a data migration framework with AWS DMS, supporting seamless transitions during technology upgrades.

· Developed dynamic data models with Toad for Oracle, supporting scalable applications in a high-growth technology environment.

· Pioneered the adoption of cloud computing platforms (Azure and AWS), enhancing data storage and processing capabilities across the organization.

· Created a JavaScript framework for real-time analytics visualization used across the organization.

· Led the development of a Java-based application for workflow management that improved process efficiency.