Interpreted complex data sets using SQL, R, and Python to uncover patterns, trends, and insights that informed business decisions.Utilized Informatica 6.1 for data integration and ETL processes, ensuring high-quality data transformation and movement.Conducted data cleaning and pre-processing with Data Flux, Excel, and Jupyter Notebook, resulting in accurate and reliable data for analysis.Developed and maintained interactive dashboards and reports in Tableau and Power BI to present data insights to stakeholders. Optimized SQL and NoSQL databases, improving scalability and data handling for user growth.Designed real-time data pipelines using Kafka and microservices, enabling seamless software integration.Collaborated with cross-functional teams to gather and understand data requirements, translating them into actionable insights and managing tasks using Jira.Performed statistical analysis and predictive modelling using SAS and SPSS to forecast trends and support strategic planning.Managed and optimized data storage solutions in Hadoop, Oracle 9i, and Teradata to ensure efficient data retrieval and processing.Wrote and optimized complex PL/SQL queries to extract, transform, and load data from various sources, including flat files and relational databases.Utilized Sqoop to import data from MySQL, PostgreSQL to Hadoop Distributed File System (HDFS) on a regular basis, ensuring seamless data integration.Performed aggregations on large volumes of data using Apache Spark and Scala and stored the processed data in Hive warehouse for further analysis.Worked extensively with Data Lakes and big data ecosystems, including Hadoop, Spark, Hortonworks, and Cloudera, to leverage their capabilities for efficient data processing.Worked on Spark SQL to create data frames on the data coming from HDFS with the different file formats like ORC, JSON, PARQUET, AVRO and storing the data back to HDFS.