MOUNIKA SAI

• Leveraged Azure Data Factory and Azure Cloud to successfully migrate and transform 60% of data, ensuring seamless transition from on-premises servers to cloud storage, while implementing ETL processes
• Spearheaded implementation of Kafka and Stream Sets, facilitating 80% of incremental data loading from Postgres SQL Database to Confluent Kafka, thereby enhancing real-time data streaming capabilities for analytics
• Led 75% of Snowflake database application development and maintenance initiatives, showcasing advanced Data Modeling and SQL skills; enhanced data flow efficiency by 40% and achieved 25% cost savings through streamlined processes
• Managed development of Spark applications and ETL pipelines, overseeing 90% of data extraction, transformation, and aggregation tasks, and leveraging Python and Scala for efficient processing.

Environment: Azure, Azure Data Factory, Snowflake, performance tuning, ADLS gen2, dataflow jobs, copy activity, lookup activity, Data Flow, linked services, Stream Sets, Databricks, Snow pipe, Confluent Kafka, Scala, SQL PySpark, Python, Azure Key Vaults, JIRA, GitHub.

• Spearheaded 60% of Data Warehousing lifecycle, optimizing performance through Spark and leveraging SQL for 80% of data analysis across diverse Oracle systems
• Orchestrated 70% of report structures in Power BI, utilizing PivotTables and V-Lookups for streamlined data presentation and analysis
• Led development of Mapping Documents and ETL specifications, driving 70% of project documentation needs and ensuring smooth data migration
• Contributed to 50% of Relational and Dimensional models using ERWIN, shaping database design for efficient data storage and retrieval

Environment: ERWIN, ETL, SQL, Power BI, SSIS, SSRS, Python, OLAP, OLTP, T-SQL, Oracle.

• Developed and optimized SQL Server databases, enhancing operational efficiency and enabling seamless data manipulation through ETL processes
• Utilized statistical techniques and SAS to interpret data, resulting in 20% increase in data-driven insights and supporting ongoing reporting efforts
• Improved data accessibility and integrity by acquiring and maintaining diverse data sources, reducing errors by 25% and ensuring robust data quality
• Leveraged Tableau for interactive dashboard creation and Excel for ad-hoc reporting, enhancing data visualization and comprehension by 40% and facilitating informed decision-making processes

Environment: ETL,MySQL, SSIS, SSRS, SQL, EXCEL, TABLEAU.