With 6 years of specialized experience in Data Engineering and Python Development, I have a strong foundation in designing and implementing data solutions using Azure's cloud services. My expertise includes Azure SQL, Databricks, Blob Storage, ADLS Gen2, and Azure Data Factory, with a focus on building scalable, efficient ETL pipelines and delivering end-to-end data engineering solutions.I am proficient in implementing OLTP, OLAP, and Data Warehousing (DW) technologies, transforming data using Azure Synapse Analytics and Azure Databricks, and working with large-scale data lakes on Azure HDInsight. I have hands-on experience in processing complex datasets using Spark for distributed computing, integrating real-time data through Kafka and Spark Streaming, and working with various file formats like Parquet, JSON, and CSV.I have deep experience developing data pipelines that handle data ingestion, cleansing, transformation, and storage, leveraging Azure Data Factory to automate workflows. My work also involves creating visualizations and reports through SQL, Pandas, and Python scripts for business insights.Beyond data engineering, I have a solid background in Python web development, utilizing frameworks such as Django, Flask, and FastAPI for backend systems and RESTful API development. This combination of skills allows me to handle full-stack development and ensure seamless integration between the frontend and backend.My projects have involved Azure's PaaS services, and I have a strong understanding of cloud-native architectures. I am passionate about optimizing data workflows and ensuring that the solutions I design are both reliable and scalable. With a background in Agile methodologies, I thrive in collaborative environments, driving projects from concept to completion while delivering high-quality solutions.