Yogesh Chinchane

Experience

1. Azure Data Engineer

   Infosys

   Apr 2022 — Present · Bengaluru, IN

   Exposure to Azure Data Factory (ADF), Azure Databricks, Azure Synapse and Azure Data Lakes GEN2.Collaborated extensively with cross-functional teams to diligently identify precise data requirements and skillfully developed comprehensive data models tailored for reporting and analytics purposes.Diligently constructed and consistently maintained highly efficient ADF Pipelines, proficiently extracting, transforming, and loading data from diverse sources into ADLS Gen2.Proficiently coded in SQL, Python, and Pyspark within Databricks, dynamically extracting, transforming, and aggregating data from multiple file formats, ensuring the data is analyzable and swiftly transformed into a ready-to-use format. Employed advanced techniques such as partitioning, coalescing, and strategic joins, optimizing performance significantly. Scheduled notebooks seamlessly using ADF, effectively applying dependencies between notebooks and efficiently passing parameters.Meticulously transformed and cleansed DS tables within Databricks notebooks utilizing SQL, PySpark, and Python code. Generated core layer (DWH) tables and stored them in delta format, employing MERGE to UPSERT the data into Data Lake tables.Experienced in creating triggers and automating pipelines using Azure Data Factory, streamlining data processing, and enhancing overall workflow efficiency.Implemented monitoring and alerting solutions for Azure Data Factory pipelines, enabling proactive identification and resolution of performance bottlenecks and data processing issues.Used JIRA for bug tracking and Bitbucket to check-in and checkout code changes.