Mohd Tajuddin Arshad
Senior Data Engineer at EPAM Systems | PySpark | Databricks | Azure | Azure Data Factory| SQL
- Role
- Senior Software Engineer at EPAM Systems
- Location
- Amravati, MH, IN
- LinkedIn followers
- 500 followers
About Mohd Tajuddin Arshad
Hello! I am Mohd Tajuddin Arshad, a passionate Data Engineer with over 8 years of experience in the IT sector, focusing on data engineering for the past 5 years. My expertise lies in leveraging technologies such as Spark, Python, and PySpark on Azure Databricks to design, implement, and optimize complex data pipelines. I am dedicated to creating innovative data-driven solutions that support strategic business decisions and enhance operational efficiency.Throughout my career, I have developed a strong proficiency in cloud-based data engineering, particularly with Azure Data Factory and Azure Data Lake. I have a proven track record of managing end-to-end data workflows, driving automation, and improving performance in distributed data systems. I pride myself on being a strong communicator and collaborator, leading cross-functional teams to deliver high-quality data insights that align with business goals.Key Achievements- Awarded the Best Employee Award at Blackstraw in 2022 for excellence in a cloud migration project to Azure- Successfully reduced data processing time from 1 week to just 1 hour by migrating workloads to the cloud.
Experience
Senior Software Engineer
Aug 2023 — Present · Pune, IN
Designed and implemented a Python (PySpark) framework for data ingestion andtransformation within Databricks, streamlining the data processing workflow- Deployed jobs in Databricks using Databricks Asset Bundles and integrated data workflowwith Azure Data Factory (ADF) for orchestration- Created and maintained optimized data pipelines using Databricks Workflow within theMicrosoft Azure ecosystem- Successfully built a flexible and efficient data ingestion framework, reducing processingtime and ensuring consistency in data transformation- Integrated Azure Data Factory with Databricks to enhance data orchestration, automation, and workflow efficiency- Contributed to the creation and management of a bronze data layer, consolidating multipledata sources for improved analytics.
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