SHARATH KUMAR SHIVAPURAM

Highly trained, skilled Azure Data Engineer with good experience in designing, developing, and implementing data solutions on the Azure platform. Proficient in ETL processes, data modeling, and performance tuning. Sounds Good knowledge in Azure Data Factory, Databricks, SQL Server, Cosmos DB and Azure Synapse Analytics. Strong problem-solving and communication skills, and good at programming languages like SQL and Python.

• Extracting the external data and it will be loaded in the ADLS.
• Creating the linked service for source and target connectivity Based on the requirement.
• Creating the pipelines and datasets which are deployed in ADF non-restricted
• Once it’s created pipelines and datasets will be triggered based on LOAD (HISTORY/DELTA) operations.
• Based on source (big or small) data loaded files will be processed in AZURE DATABRICKS by applying operations in spark SQL. Which will be deployed through AZURE DATA FACTORY pipelines.
• Involved in setting up the environments for TEST.
• Migrated data from Client data scope to Azure SQL server and Azure Data Lake Gen2. Development of Data Bricks Note Books using SQL, Python.
• Developed Pipelines in Azure Data factory using Multiple Activities.
• Having good knowledge 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.
• Deep idea about in migration of existing solutions On-Premise systems/applications to Azure cloud.
• Trained on AzureSuite: Azure SQL Database, Azure DataBricks(ADB), Azure Data Lake (ADLS), Azure Data Factory (ADF) V2, Azure SQL Data Warehouse.
• Well versed knowledge in creating pipelines in Azure Cloud ADFv2 using different activities like Data Bricks, Copy, Filter, ForEach, Move &Transform etc.
• Extract data from on-premise and cloud storages and Load data to Azure Data lake from On[1]Premise Databases, Azure SQL Databases, ADLS Gen 1, ADLS Gen 2, Azure BLOB Storage using Both + 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).
• In the process of training, I have 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.
• 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, upset which made ADF Code Free and well compatible with SSIS Transformations.
• The ADF Pipelines are made Dynamic with Parameters, Expressions, Functions and Column Patterns.
• Having good knowledge in Microsoft Azure Cloud Services ( PaaS & IaaS ), Application Insights, Document DB, Internet of Things (IoT), Azure Monitoring, Azure Synapse Analytics Key Vault, Visual Studio Online (VSO) and SQL Azure.
• In the process of training I have Created Data frames in Databricks and applied various transformations like string functions, aggregations, window functions, Filtering, Splitting, Renaming, Removing duplicates etc.
• Good Practical knowledge on Informatica Power Center tools- Designer, Repository Manager, Workflow Manager, and Workflow Monitor.
• Some of the SSIS Packages are Deployed into Cloud from On-Premise with “Lift and Shift” after making Minimum Configuration Changes.

§Excellent communication skills with excellent work ethics and a proactive team player with a positive attitude. Domain Knowledge of Finance, Logistics and Health insurance.