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Data Engineer with expertise in Python, SQL, and Databricks, experienced in designing end-to-end data pipelines on Azure and AWS. Proficient in Azure DevOps, DABS, and Power BI, with a focus on scalable architecture, data quality, and performance optimization.…

Phani Ch

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Data Engineer with expertise in Python, SQL, and Databricks, experienced in designing end-to-end data pipelines on Azure and AWS. Proficient in Azure DevOps, DABS, and Power BI, with a focus on scalable architecture, data quality, and performance optimization.…

Available to hire

Data Engineer with expertise in Python, SQL, and Databricks, experienced in designing end-to-end data pipelines on Azure and AWS. Proficient in Azure DevOps, DABS, and Power BI, with a focus on scalable architecture, data quality, and performance optimization.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Work Experience

Data Engineer at The Marketing Store

August 1, 2022 - Present

Proficient in Azure cloud platform with in-depth expertise in Databricks, Azure Data Factory, and Blob Storage; designed, developed, and maintained robust data solutions; built ETL pipelines using PySpark on Databricks to process and transform large volumes of data from diverse sources; implemented pipelines using Databricks Asset Bundles to improve CI/CD, environment separation, and version control; developed and orchestrated data pipelines in Azure Data Factory for ingestion and transformation of structured and semi-structured data; hands-on experience with AWS ETL services including Lambda, S3, Glue, Redshift, and Step Functions; designed and implemented large-scale data pipelines using AWS Glue, improving data processing efficiency by 20%; used Dev Endpoints for development and testing of custom ETL scripts; collaborated with cross-functional teams to translate business requirements into efficient data solutions and dashboards.

Data Engineer at Corel Corporation

August 1, 2021 - July 1, 2022

Developed end-to-end data project on Recurly using Python and advanced SQL. Implemented a data pipeline that extracts data from multiple sources, transforms millions of rows, and loads into S3, making it queryable via Redshift. Maintained data pipeline uptime of 99.9% while ingesting transactional data across diverse primary sources using Spark, Redsift, S3, and Python.