Vedasree Kommindala

Project Trade Vault:

• Involved in extracting data from diverse sources such as ERP systems, SQL Server, AWS S3 and others into Snowflake.
• Involved in reviewing existing SSIS and SSRS packages to identify equivalent snowflake tools and functionalities for migration.
• Utilizing Matillion for ETL processes for extracting data from Snowflake, applied data transformations for cleansing, filtering, aggregations and loaded transformed data back into Snowflake in Python.
• Developing and maintaining complex SQL stored procedures for data transformation, validation, and business logic implementation to ensure data accuracy and consistency.
• Google Analytics and BigQuery are leveraged to track and analyze user behavior, including calculating user time on site and engagement metrics across various web pages and product categories.
• Worked closely with analysts, and business stakeholders to understand data requirements, create Tableau dashboards and deliver solutions.

Project USMCA:

• Used AWS S3 as the initial storage layer for raw data coming from various sources like RPA, file servers, SAP.
• Developed custom Python scripts to move data between S3, DBFS and Redshift and
• within Alteryx workflows to perform advanced data cleaning and aggregation, optimizing the ETL process and improving data accuracy.
• Implemented ETL pipelines by transforming Alteryx workflows into Databricks Spark Scala jobs to process raw data into structured formats.
• Utilized scala, SQL and conducted comprehensive performance analysis and optimization exercises for existing code improving efficiency.

• Worked alongside the data Architect and DevOps team to assist in the development and maintenance of ETL processes for data extraction, transformation, and loading
• Applied data cleansing (e.g
• Flagging invalid, duplication) for ingested tables
• Gained hands-on experience with Azure Data Factory, Azure Databricks, and various azure services, contributing to the optimization of data pipelines
• Assisted in troubleshooting and resolving data-related issues to ensure data quality
• Worked on POC developing microservices using Java, Kafka cluster setup and deployed Flink jobs for processing real time data pushing and visualizing data to RDBMS and ELK stack
• Designed and developed SSIS packages to move data from various sources into destination flat files and databases
• Developed scalable data processing pipelines using PySpark & Python to perform batch and streaming data transformations and analysis

• Utilized PL/SQL, Spark scala built jars, PySpark and Spark SQL that run on Dataproc to extract & transform monthly quantitative data according to business needs and loaded back in hive tables
• Created data products from available data to cater business needs
• Developed and maintained data processing pipelines using Google Cloud Dataflow to efficiently transform and load large datasets into the data warehouse
• Built scalable data warehousing solutions using BigQuery, integrating diverse data sources, including APIs, third-party tools, and on-premises systems, to centralize business intelligence reporting
• Use of BigQuery for Query Execution plan, Efficient schema design, Optimization techniques, Partitioning and Clustering
• Managed and scheduled Jobs on cluster using Composer and Airflow workflows using Python
• Experience with CI/CD pipelines and oozie workflow deployment

• Developed e-commerce web applications for clothing using HTML, CSS and React were used for front-end side and MySQL database and PHP as back end
• Documentation of all work done during project development