As a Data Engineer at Larsen & Toubro, I delivered data solutions within the Microsoft Azure ecosystem, using my strong problem-solving skills and solid technical foundation. I developed and implemented Azure Data Factory pipelines to automate data ingestion from four project sites, defined and ensured data quality checks, cleaned and joined diverse datasets using Azure Databricks, and loaded final data into SQL Database for access by data analysts. These data-driven solutions yielded impressive results, such as a 50% increase in receivables, a 40% faster project execution, and a 40% improved data analysis workflow.I hold a Master's in Big Data Analytics from Trendy Tech and a Master of Technology in Construction Management from IIT Delhi. My education background and proficiency in Python, SQL, and PySpark equip me to navigate the world of Big Data technologies and cloud solutions. I'm adept at data ingestion, transformation, and analysis using tools like Azure Data Lake, Databricks, Data Factory, and Synapse Analytics. I have an extensive knowledge in Lakehouse Fundamentals, Delta Lake optimizations, and Data Warehousing principles.In addition to Azure, I have hands-on experience in Microsoft SQL Server, Postgresql and MySQL Database Management Systems, as well as Hadoop Technologies like HDFS, Apache Spark, and Apache Hive. I also have knowledge of Business Intelligence (BI) and how to apply them to various data scenarios.I'm passionate about building business-driven solutions that seamlessly connect data and business needs, and I'm always eager to learn new technologies and skills. I'm seeking Data Engineer or Big Data Cloud Developer roles that challenge and utilize my diverse skills across the ETL pipeline, and that align with my values of innovation, collaboration, and ethics.
