Krishna Rao Email & Phone Number

• Over 9+ years of expertise in Analysis, Design, and Development of data platform on Cloud with high-quality Data Modelling, design, and development of Data Pipelines to ingest, store and transform data for data analytics and systems integration.• Experience in migration of existing solutions On-Premise systems/applications to Azure cloud.• Worked on Azure Suite: Azure SQL Database, Azure DataBricks(ADB), Azure Data Lake (ADLS), Azure Data Factory (ADF) V2, Azure SQL Data Warehouse.• Highly experienced in using Multi Cloud Services to achieve maximum efficiency and performance for data application, used Azure platform for building extensive data pipelines for doing terra scale of data analysis.• Extract data from on-premise and cloud storages and Load data to Azure Data lake from On-Premise Databases, Azure SQL Databases, ADLS Gen 1, ADLS Gen 2, Azure BLOB Storage using Both ETL and ELT Fashion using Azure Data Factory(ADF) and Azure DataBricks(ADB) and PolyBase feature in SQL 2016 using External Tables.• Moved SSIS packages from On-premise to cloud using Azure Data Factory(ADF) and Azure DataBricks(ADB).• Created Pipelines in ADF using Linked Services/Datasets/Pipeline/ to Extract, Transform and load data from different sources like Azure SQL, Blob storage, Azure SQL Data warehouse, write-back tool and backwards.• Implemented and gained knowledge on Many New ADF Mapping Data Flow Components like New Branch, Join, Conditional Split, Exists, Union, Lookup, Derived Column, Surrogate Key, Window, Filter, Sort, Alter Row, For Each loop, Upsert which made ADF Code Free and well compatible with SSIS Transformations. • The ADF Pipelines are made Dynamic with Parameters, Expressions, Functions and Column Patterns.• The ADF Pipelines are Scheduled using Triggers and Monitored the Performance and Execution In Monitoring Logs and Dashboards.• Created DataBrick Notebooks using Python, Scala and Spark SQL to read and write JSON, CSV and Parquet files.• Created Dataframes in Databricks and applied various transformations like string functions, aggregations, window functions, Filtering, Splitting, Renaming, Removing duplicates etc• Used various complex data types like Structs, Arrays, Maps, Lists in Pyspark to handle complex data and flattened them using Split and explode• Optimized Databricks notebooks tuning cluster configurations, Repartitioning, join types, Shuffling configurations, Memory settings and caching.

Listed skills include Core Java, Javaserver Pages, Data Warehousing, Requirements Analysis, and 27 others.