With over 9 years of professional experience in the full Software Development Life Cycle (SDLC) and Agile methodologies, I have a proven track record in analysis, design, development, testing, implementation, and maintenance of big data technologies, including Spark, Hadoop, Data Warehousing, and Scala. I have extensive experience migrating SQL databases to Azure platforms, including Azure Data Lake, Azure SQL Database, Azure Data Lake Analytics, and Azure SQL Data Warehouse. My expertise lies in building near-real-time pipelines using Kafka and PySpark, designing cloud-based solutions in Azure, and creating efficient data workflows with Azure SQL Database, Elastic Pool Jobs, and Azure Analysis Services. Additionally, I have developed and orchestrated robust data pipelines using Azure Data Factory, Apache Oozie, and Apache Airflow, while ensuring the successful migration and control of on-premises databases to Azure Data Lake Store.I am proficient in various programming languages such as Python, PySpark, Scala, and SQL, with strong experience in data manipulation using Spark APIs, Spark SQL, and MapReduce for big data analysis. My background includes working with Apache Hadoop, Spark MLlib, Flume, and NiFi for log file ingestion, as well as expertise in NoSQL databases like HBase and Cassandra. I am adept at developing and optimizing ETL/ELT processes using SSIS, Matillion, AWS, and Snowflake, with hands-on experience in performance tuning, automation, and building enterprise data warehouses. My strong foundation in data platforms extends to designing star schema and ODS architecture, dimensional data modeling, data governance, and metadata management. With solid analytical and problem-solving skills, I thrive in cross-functional team environments, contributing to the completion of large-scale projects and delivering cutting-edge solutions for complex data challenges.