● Developed and implemented stored procedures to streamline data processing tasks, improving operational efficiency and accuracy.● Utilized SQL Server Integration Services (SSIS) to automate the extraction, transformation, and loading (ETL) of large datasets from various environments to on-premises systems.● Designed and created interactive MDS dashboards in IBM to enable users to manage and visualize data effectively.● Executed comprehensive data analysis processes, ensuring accurate data migration and transformation while maintaining data integrity.● Performed data cleaning and validation to enhance the reliability and usability of datasets across multiple platforms.● Automated data import and export processes, significantly reducing manual workload and minimizing errors in data handling.●Utilized C# and shell scripting to automate repetitive tasks, enhancing the efficiency of data extraction from Active Directory.●Ensured synchronization accuracy and improved data accessibility through automation of Active Directory data retrieval processes.● Designed and implemented ETL workflows snowflake tailored to meet complex data movement requirements within the organization.● Developed Hive Data Definition Language (DDL) scripts for creating, altering, and dropping Hive tables to optimize data structures.●Collaborated with stakeholders to define and implement business rules for data governance and management.●Created approval workflows for update and delete processes within Master Data Services (MDS) to ensure data integrity and compliance.● Managed user permissions at the administrative level, facilitating secure access to data and resources.●Built insightful reports and dashboards using Power BI and SQL Server Reporting Services (SSRS) to provide actionable business insights.●Maintained version control and documentation of projects using Bitbucket, fostering collaboration and transparency within the team.

● Designed and implemented data pipelines to ingest large datasets from sources like AWS S3, HDFS, Kafka, and external APIs, automating data intake processes for seamless integration into Amazon Redshift and Snowflake.● Utilized PySpark and Spark SQL to clean and transform raw data into structured, usable formats, applying transformations to enrich data, ensuring accuracy and consistency before storing in the data warehouse.● Optimized Amazon Redshift and Snowflake data storage and retrieval for improved reporting and analytics, designing efficient schemas and applying data modeling best practices to enhance performance and scalability.● Developed and orchestrated ETL/ELT workflows using Apache Airflow, automating data extraction, transformation, and loading processes, and configuring DAGs for seamless execution and monitoring of scheduled data jobs.● Integrated Apache Spark with Kafka to process and analyze streaming data in real-time, enabling timely data updates for flight performance, customer service, and marketing insights.● Leveraged AWS Lambda for event-driven data processing, automating data loads into Redshift when new files arrived in S3, and increasing operational efficiency through serverless architecture to minimize manual intervention.● Led data migration from on-prem systems to AWS Redshift and Snowflake, ensuring no data loss and smooth synchronization, and implemented scalable data migration strategies for cloud-based operations.● Worked closely with marketing, loyalty, and operations teams to understand data requirements and deliver tailored solutions, translating business needs into technical specifications to align with United Airlines' strategic goals.● Developed automated data validation frameworks to ensure data quality and integrity, conducting data audits and applying quality checks to ensure reporting accuracy.● Integrated Docker and GitHub for CI/CD, streamlining the deployment of data pipelines and solutions.

● Designed and implemented ETL pipelines for large-scale data integration, leveraging SQL Server, Oracle, Teradata, and DB2, ensuring seamless extraction, transformation, and loading (ETL) of data from multiple sources into centralized data systems for analysis.● Utilized PySpark and Python to automate data transformation and processing, enabling the ingestion of both structured and semi-structured data for energy-related analytics and reporting.● Built and optimized data pipelines using Informatica PowerCenter and SSIS, automating data flows for energy data extraction, transformation, and loading into target data stores like Netezza, improving accessibility for reporting and analysis.● Worked with cloud technologies like AWS and Azure to integrate and manage data storage and processing, ensuring scalability and reliability for large-scale energy consumption and operational data analysis.● Developed and maintained data models using ER/Studio, ensuring the proper design of data structures for efficient storage and retrieval, and improving performance for both analytics and reporting.● Automated data validation and quality assurance processes using Python and SQL, developing scripts to identify and address data integrity issues, ensuring accurate reporting for business stakeholders.● Processed data from IoT devices and external feeds (e.g., JSON, XML) using custom parsers, ensuring that energy-related data was transformed into usable formats for analysis and decision-making.● Created and maintained REST APIs to streamline data access across internal and external systems, facilitating real-time data processing.● Applied pushdown optimization and dynamic SQL techniques to improve data processing performance, reducing ETL job run times and ensuring faster data availability for business users.● Analyzed large datasets and created actionable insights using SQL and data visualization tools (e.g., Tableau, Power BI), providing regular reports on energy consumption.

● Participated in cost containment projects to achieve stated savings and explore new opportunities, driving cost reduction through data insights and analytics.● Partnered with global stakeholders across Network, FWA, Clinical, and Operations to align analytics outcomes with organizational objectives and business needs.● Prepared and presented strategic and tactical analytics using Tableau and QlikView to managerial and front-line partners, promoting improvements in customer experience and healthcare cost management.● Presented data insights to identify key improvement opportunities, savings opportunities, and case management strategies, with a focus on reducing costs and improving clinical outcomes.● Developed predictive models using Python (Scikit-learn, TensorFlow) to forecast medical costs, clinical outcomes, and care provider performance for more accurate decision-making.● Developed insights into member and care provider performance, identifying key variables impacting healthcare outcomes and cost efficiency.● Enhanced Cigna’s Reasonable & Customary (R&C) medical cost structure, aligning with Cigna’s affordability strategy to drive incremental value.● Managed data consolidation and analytics to support the creation of an R&C reference model for designated regions, ensuring consistency with global standards and local healthcare environments.● Defined and standardized the R&C framework, including designing user databases and translating them into actionable workstreams for execution.● Gathered and integrated data from multiple sources (SQL, Python, Tableau, Excel) into global dashboards and reports, ready for presentation to senior leaders.

● Involved in creating logical and physical data analyst with STAR and SNOWFLAKE schema techniques using Erwin in Data warehouse as well as in Data Mart● Performed data analysis and data profiling using complex SQL on various sources systems including Oracle, Netezza and Teradata● Involved in Data Analysis, Data Validation, Data Cleansing, Data Verification and identifying data mismatch● Writing and executing customized SQL code for ad hoc reporting duties and used other tools for routine● Extensively used SQL to develop reports from the existing relational data warehouse tables (Queries, Joins, Filters, etc)● Migrated SSIS packages from SQL Server to SSIS and Created Mappings for Initial load from MS SQL server 2005 to Netezza while performing data cleansing● Converted SQL Server packages to Informatica Power Center mapping to be used with Netezza and involved in Informatica MDM processes including batch based and real-time processing● Performed ad-hoc queries by using SQL, PL/SQL, MS Access, MS excel and UNIX to meet business Analyst's needs● Responsible for reviewing data model, database physical design, ETL design, and Presentation layer design● Conducted meetings with business and development teams for data validation and end-to-end data mapping● Developed logging for ETL load at the package level and task level to log number of records processed by each package and each task in a package using SSIS● Involved in Oracle, SQL, PL/SQL, T-SQL queries programming and creating objects such as stored procedures, packages, functions, triggers, tables, and views● Performed match/merge and ran match rules to check the effectiveness of MDM process on data