• Developed secure and cost-efficient data solutions for clients in various industries like Finance, Product, and Retail using Python.• Created data pipeline jobs, scheduled triggers, and migrated databases to Azure Data Lake Storage and Snowflake data warehouse.• Utilized Spark Architecture, Spark SQL, and Data Frames for SQL query analysis and Excel data processing.

Orchestrated the creation of linked services to facilitate seamless connectivity between source and target systems, customized to meet project requirements.2. Engineered robust pipelines and datasets within Azure Data Factory, meticulously ensuring compliance with industry best practices and project specifications.3. Established connections from diverse sources, including On-Premise and cloud environments, consolidating them into a singular source for Power BI reports.4. Conducted thorough cost analyses to pinpoint areas for potential savings and spearheaded initiatives to enhance profitability.5. Designed and developed interactive dashboards and reports using Power BI, leveraging insights derived from data extracted from OLTP and OLAP sources via Azure Data Factory and Databricks.6. Demonstrated proficiency in database management with Snowflake, Python, and MySQL, adeptly utilizing SQL statements and implementing advanced SQL concepts such as JOINS, WINDOW FUNCTIONS, COMMON TABLE EXPRESSIONS (CTE), and CASE STATEMENTS.