Kunal Sawant

About Kunal Sawant

Azure Data Engineer | Turning Data into Scalable Cloud SolutionsWith 3.5+ years of hands-on experience at Infosys, I specialize in designing and delivering scalable, secure, and high-performance data solutions on Microsoft Azure. I am passionate about transforming raw data into reliable, analytics-ready assets that enable smarter business decisions and measurable growth.I bring strong expertise in building end-to-end data pipelines, optimizing cloud architectures, and implementing efficient ETL/ELT frameworks using modern Azure data services. Core Technical Expertise Azure Data Factory (ADF) – Designing and orchestrating robust data pipelines, managing complex workflows, and enabling seamless data integration across multiple sources. Azure Databricks – Developing scalable ETL solutions using PySpark for large-scale data processing and performance optimization. Azure SQL Database & Synapse Analytics – Data modeling, performance tuning, query optimization, and building enterprise-grade cloud data warehouses. Python – Automation, data transformation, and advanced data manipulation using Pandas and related libraries. SQL – Writing complex queries, optimizing ETL processes, and ensuring high data quality and integrity. Functional Strengths Building scalable ETL/ELT pipelines using Azure ecosystem Designing secure cloud data architectures Implementing data warehousing and lakehouse solutions Supporting analytics and reporting for business intelligence Performance tuning and cost optimization in cloud environments I thrive in dynamic environments where data drives strategy. My goal is to contribute to impactful, data-driven initiatives by delivering reliable, scalable, and efficient cloud data solutions.If you\'re looking for a Data Engineer who combines technical depth with practical implementation experience, let’s connect.

Experience

1. Senior Data Engineer

   Infosys

   Jan 2024 — Present · Pune, IN

   Designed and implemented end-to-end data pipelines using Azure Data Factory (ADF) to ingest structured and semi-structureddata from on-premise systems, APIs, and automotive telematics sources into Azure Data Lake Storage Gen2.• Built and maintained a Medallion Architecture (Bronze, Silver, Gold layers) using ADLS and Azure Databricks to enable scalable,modular, and reliable data processing.• Developed PySpark-based transformation logic in Azure Databricks to cleanse, standardize, and enrich raw automotive datasets(vehicle diagnostics, sensor data, warranty claims).• Optimized data processing performance by implementing partitioning, caching, Delta Lake optimizations (Z-ordering, vacuum,auto optimize), reducing query time by up to 30%.• Designed curated Gold layer data models to support Power BI dashboards for fleet performance, predictive maintenance, andsales analytics reporting.• Implemented CI/CD for data pipelines using Azure DevOps, enabling automated deployment of ADF pipelines, Databricksnotebooks, and infrastructure across Dev, QA, and Prod environments with version control and release management.• Performed root cause analysis and performance tuning of Spark jobs by optimizing joins, broadcast strategies, file sizes, andcluster configurations, resulting in improved pipeline stability and reduced execution cost.

Education

• Atharva College of Engineering

  Bachelor of Engineering - BE, Computer Engineering