Experience

• 

  Planify.in

  Jun 2018 - Aug 2018

  Back end software developer- intern

  I helped in creating one of the complex WorkModules of the company. I helped in creating in Api using SpringBoot And Gradle for the company.I was also Awarded with the Planifier Excellence Award(given to the intern who outperforms other interns during his time period of internship in the company)

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  Maq software

  Jan 2020 - May 2022

  Beverage Sales Reporting• Gathered Requirements to kick-start the project• Created azure data pipelines to pull data from the latest modified data from SharePoint.• Performed ETL operations on data using M Query in azure analysis server.• Performed Error Analysis and notified users about the errors in different data files.• Created a tabular model on an azure analysis server with measures using Dax query.• Created dynamic power bi report to generate insights using visuals and measures.• Conveyed insights to business counterparts on a daily basis. Healthcare Management System• Performed Exploratory data and gathered requirements to start the project.• Created a benchmark process to rank hospitals within their competition.• Performed Outlier analysis• Created what-if analysis with the help of multiple regression.• Create pipelines in azure data factory to automate the complete process Show less Data Analysis Using Statistical Model ▪ Performed ETL Operations on data collected from multiple source. ▪ Performed Exploratory Data Analysis using the model to generate Insights. ▪ Created a statistical model Using Random Forest Classifier. ▪ Analyzed and Validated the Result generated from the model. ▪ Created Reports Using Power BI to represent the Insights Generated. ▪ Automated the whole process by Establishing pipelines in Azure Data factory. ▪ Eliminated Manual Testing Procedure and reduced validation time by 80%(2 hrs. from 10 hrs.) ▪ Implemented and handled Migration of on-premises database to the cloud server. Show less

  • Software Engineer 2

    Mar 2022 - May 2022

  • Software Engineer 1

    Jul 2020 - Mar 2022

  • Software Engineer Intern

    Jan 2020 - Jul 2020
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  Algoscale

  Jun 2022 - Oct 2023

  Data engineer

  1. Designed and implemented end-to-end data ingestion pipelines using Azure Data Factory (ADF) to extract data from various sources like SAP HANA, MySQL, SQL Server, and Azure Blob Storage, and stored it in the raw layer for processing.2. Developed scalable ETL processes in PySpark and Pandas on Azure Databricks, performing data cleaning and transformations to prepare datasets for the silver/gold layer, ensuring consistency and quality in the data.3. Automated dynamic configurations for ADF linked services and activities, with real-time configurations pulled from SQL database tables, allowing reuse of pipelines across multiple data sources and clients.4. Implemented incremental data loads with full refresh capability, leveraging watermark timestamps stored in SQL databases to track and update data refreshes efficiently, ensuring accurate and up-to-date data in the pipeline. Show less

• 

  Multplyr

  Oct 2023 - now

  Data engineer

  1. Designed and implemented a scalable data model and ingestion framework to handle schema changes seamlessly across datasets, ensuring uninterrupted pipeline operations for multiple clients.2. Built a YAML-driven configuration system for data pipelines, enabling flexible customization of data sources, transformations, and processing rules without code changes, improving onboarding speed for new customers.3. Developed reusable PySpark wrapper functions, streamlining data processing by allowing dynamic customization across multiple clients and use cases, reducing code duplication and enhancing efficiency.Implemented high-performance data lakes on HDFS, achieving a 20% boost in data processing speed and a 30% reduction in storage costs.4. Introduced a data quality check mechanism that reduced data anomalies by 20%, improving data accuracy.5. Collaborated with 10+ data scientists and engineers, reducing data-related delays by 40% through efficient troubleshooting and defining data requirements.6. Consolidated data from 20+ sources, ensuring 99.9% accuracy with automated data cleansing and quality checks.7. Integrated CI/CD practices to automate data pipeline deployments and maintain data quality. Show less