Sravan Kumar Email & Phone Number

● Created ETL pipelines using Python, Spark, PySpark and Hive to process data and load it into Oracle and S3.● Work on database upgrade activities and create automated jobs to validate data / structures between old and new databases.● Test various processes and support different models and releases for Actimize and load the input data for validations into prod-beta environments to test compatibility and performance.● Provide performance tuning for the existing jobs and redesign if required.● Support upgrade activities by coordinating with multiple teams for setup of environment and services.● Build data pipelines using Data Proc and Dataflow in GCP for ETL related jobs.● Worked on GCP data-proc cloud platform to process huge volume datasets.● Used cloud shell SDK in GCP to configure the services Data Proc, Cloud Storage, BigQuery.● Worked with google data catalog and other google cloud APIs for monitoring, query, and billing related analysis for BigQuery usage.● Carried out data transformation and cleansing using SQL queries, Python and Pyspark.● Coordinating with team and Developed framework to generate Daily adhoc reports and Extracts from enterprise data from BigQuery.● Wrote scripts in Hive SQL for creating complex tables with high performance metrics like partitioning, clustering, and skewing.● Worked on downloading Big Query data into pandas or Spark data frames for advanced ETL capabilities.

● Developed ETL pipelines to consolidate multiple data sources.● Optimized SQL queries for faster retrieval of data● Created data models for OLAP and OLTP systems using ER modeling and dimensional modeling techniques.● Developed conceptual, logical, and physical data models using data modeling tools like Erwin.● Implemented distribution strategies, indexes, partitions, and keys for optimal performance levels.● Collaborated with BI and Analytics teams on creating the semantic layer.● Established standards and guidelines around modeling of dimensional, semantic and data mart layer.

● Implemented a Python-based distributed random forest via PySpark and MLlib.● Created and maintained reports to display the status and performance of deployed model and algorithm with Tableau.● Created SSIS package to load data from Flat files, Excel and Access to SQL server using connection manager.● Develop all the required stored procedures, user defined functions and triggers using T-SQL and SQL.● Produced report using SQL Server Reporting Services (SSRS) and creating various types of reports.● Extensively involved in all phases of data acquisition, data collection, data cleaning, model development, model validation, and visualization to deliver data science solutions.● Built machine learning models to identify fraudulent applications for loan pre-approvals and to identify fraudulent credit card transactions using the history of customer transactions with supervised learning methods.