•Created a process for loading the data from different sources to target tables in the concept of one readand one write for loading it into multiple layers. This reduced the efficiency of the data loading andprevented multiple reads & writes from different locations.•Worked on Data Quality validations (QA) using the unified approach for delivering accurate results.•Created Shell scripts for bringing the on-premises data to Azure and implemented the error handlingtechniques.•Implemented scripts for a unified batch handler process that loads data into silver, refined, and refresheddata in Snowflake.•Experience in ADF, ADB, Storage accounts, CI/CD best practices, unity catalog, and wrote scripts forreusable & efficient data loading.

• Created ETL pipelines using microservices for loading the data from Redshift to S3 buckets in the form of parquet files which are used by the Analytics team for reporting.• Performed continuous development, Integration and thus perform frequent releases.• Coordinated with upstream and downstream and regularly take daily stand-ups and weekly meet-ups to reduce last-minute production issues.• Performed tuning of SQL queries and it accelerated server performance.• Programming Language, Tools & Technologies used: Redshift, Github, Postman, JIRA, Elastic Search, JSON, Python, Linux and Unix Commands, SQL, Excel, Jenkins.

• Collected and cleanse the data from various sources and stored it in a Data warehouse (DWH) which was further used for building data marts and reporting purposes used by businesses.• Monitored flows that run on On-premise and Bigdata Environments, where streaming data is loaded using Data Lake, and maintained 96% of data available to clients on daily basis. • Fixed complicated data-related issues like Cannot place a NULL value in the NOT NULL field, Duplicate data, Numeric Overflow, Bad Character, and other issues like Connectivity issues, File missing issues which blocked the production Data.• Analysis of Execution Plan, Tuning SQL Query to optimize queries and enhance the performance of databases.• Generated ad-hoc-reports in excel Power Pivot and shared them with the team for incident reduction and for Strategic planning of reducing the team effort in frequent issues.• Programming Language, Tools & Technologies used: Informatica Power center, Hive, Oozie, Teradata, Maestro Scheduling tool, Abinitio, Shell Scripting, Linux, and Unix Commands.

• Evaluated existing On-premise model and replicated it on Microsoft Azure.• Designed and created pipelines for data ingestion using cloud-native services ADF, Azure Data Lake, ADB, and Azure SQL to desired data formats.• Created JSON files for enabling dynamic loading of data, without unnecessarily creating multiple resources. • Executed Pyspark Transformations which helped in data modeling and in data retrieval. • Programming Language, Tools & Technologies used: Azure Data Factory, ADLS, Azure SQL, Azure Data bricks, Azure Key Vault, SQL Server Management Studio.