Ankitha Nalleboina

Senior Data Engineer @Wells Fargo

Designed and developed scalable ETL workflows in Azure Data Factory (ADF) and Databricks, processing large datasets efficiently and optimizing data flow for large-scale analytics.• Built and maintained data lake architecture in Azure Data Lake to support large-scale analytical workloads, ensuring smooth data integration from multiple sources.• Integrated third-party APIs and external data sources into Azure Data Lake to enrich insights and enhance data processing pipelines.• Developed incremental data loading strategies in Azure Data Factory (ADF) and Databricks to improve processing efficiency and reduce data pipeline execution times.• Automated data lineage tracking in Azure Data Factory to enhance data traceability and compliance reporting, ensuring data transparency across pipelines.• Optimized SQL queries and indexing strategies in SQL Server and Azure Synapse Analytics to enhance data retrieval performance and reduce query execution times.• Created data partitioning and indexing strategies in Azure Synapse Analytics to optimize query performance, enabling faster data processing for large datasets.• Developed real-time data ingestion frameworks using PySpark, Databricks, and Azure Data Lake, enabling seamless data integration and reducing latency in data processing.• Built custom data ingestion frameworks in Databricks and ADF to handle complex business transformations and ensure data consistency.• Ensured data security and compliance by implementing encryption and access control measures in Azure Synapse Analytics, ADF, and Databricks.• Implemented data governance frameworks to standardize data definitions, ensure data quality, and maintain compliance, particularly in Synapse Analytics.• Automated ETL job execution logs and implemented automated failure alerts in Azure Data Factory (ADF) and Databricks to improve pipeline reliability.