As a seasoned Senior Data Engineer with over 7.5 years of extensive and diverse experience, I specialize in delivering innovative solutions across various domains and industries. My expertise lies in data modeling, designing, and maintaining ETL pipelines using leading cloud services such as Azure and AWS, along with big data technologies like Hadoop, Kafka, and Spark.Throughout my career, I've demonstrated proficiency in a wide array of cloud services including Azure Data Factory, Databricks, AWS services like Athena, Glue, Lambda, and more. I have a strong command over SQL databases such as MySQL, SQL Server, as well as NoSQL databases like DynamoDB, CosmosDB, and OracleDB. Additionally, I've leveraged data warehouses like Azure Synapse, AWS Redshift, and Snowflake, and have adeptly created impactful dashboards using visualization tools like QuickSight, Tableau, and Power BI.My automation skill set includes expertise in Airflow, Bash scripting, and Cron jobs, enabling me to streamline workflows effectively. I'm well-versed in Spark applications, SQL, PySpark, Agile methodologies, and have a track record of building strong relationships with stakeholders and architecture teams. Moreover, my proficiency extends to Hadoop ecosystem components and CI/CD pipeline tools.Certified in Python and SQL, I hold credentials in Python for Data Science, Data Analysis with Python, and Introduction to Data Science from reputable institutions. My project experience spans various roles, including Senior Data Engineer and Data Scientist consultant. In these roles, I've tackled responsibilities ranging from designing and developing Azure Data Factory pipelines to implementing real-time stream analytics through Amazon Kinesis Data Analytics.With a demonstrated history of delivering successful projects and driving business value through data-driven insights, I am passionate about leveraging my skills and experience to contribute effectively to challenging projects in the field of data engineering and analytics.