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Results-driven Data engineering professional with solid foundation in designing and maintaining scalable data systems. Proficient in Aure cloud and Pyspark, SQL, Python and Cloud based platforms. Known for strong collaborative skills and ability to adapt to dynamic project requirements, delivering reliable and timely solutions.


  Over 5 years of experience as a Data Engineer with expertise in building scalable data pipelines, data lakes, and ETL processes using Python, SQL, and Big Data technologies on AWS, Azure, and GCP platforms.
  Proficient in designing robust data architectures, implementing data integration strategies, and optimizing data workflows to support advanced analytics and data-driven decision-making.
  Hands-on experience with cloud platforms including AWS (EC2, S3, RDS, Lambda), Azure (Data Factory, Data Lake, Databricks), and GCP (BigQuery, Dataflow).
  Skilled in CI/CD pipeline development using Jenkins, Docker, Kubernetes, and Terraform to ensure efficient deployment and automation.
  Strong knowledge in data modeling, data warehousing, and creating data visualizations using Power BI and Tableau.
  Proven ability to work in Agile and Waterfall environments, delivering high-quality solutions within project timelines.


 As a Data Engineer, I work on setting up data platforms for clients who need to grow and adapt in the digital world. I develop assets for ingesting data from various source systems and automate the process using Azure services. I also manage complex and compounding datasets to maximize the value of data for business insights and decision making. I have a strong background in data engineering, with multiple certifications in Azure, AWS, GCP, and Databricks. My goal is to leverage my expertise in data engineering and data science to provide innovative and scalable solutions for complex data challenges. 

Cloud Data Engineer with over 4 years of experience designing and implementing scalable data pipelines, cloud-based data warehousing, and real-time analytics solutions. Proficient in Microsoft Azure, AWS, and Apache Spark (PySpark, Scala) with expertise in Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) frameworks. Skilled in orchestrating workflows using Apache Airflow and optimizing data processes for business intelligence. Experienced in collaborating with stakeholders to deliver data pipelines that improve processing speed and data governance.

Tejas Gavali

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Infosys Limited

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Sir Visvesvaraya Institute of Technology
Nashik, Maharashtra

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Azure Data Engineer

Sir Visvesvaraya Institute of Technology

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