Baltha Reddy
- Role
- Azure Data Engineer Architect at Tata Consultancy Services
- Location
- Stamford, CT, US
- LinkedIn followers
- 500 followers
About Baltha Reddy
At Tata Consultancy Services, my expertise in architecting robust data solutions has been…
Experience
Azure Data Engineer Architect
May 2024 — Present · Stamford, CT, US
Design, implement, and maintain data solutions in Azure.• Managing Delta Lakes for scalable and performant data storage solutions, enabling ACID transactions and efficient data versioning.• Designed and implemented data pipelines using Microsoft Fabric for seamless integration and transformation of data from diverse sources.• Built Lakehouse architecture within Microsoft Fabric to unify data storage and analytics workflows for efficient reporting and insights.• Developed and optimized ETL pipelines using Dataflow Gen2 to load and transform large datasets into OneLake for downstream processing.• Integrated Power BI with Fabric to deliver interactive dashboards and visualizations for enterprise-wide data insights.• • Migrated legacy data solutions to Microsoft Fabric’s modern data ecosystem, improving operational efficiency and reducing costs.• Enhanced data governance and security by implementing role-based access control (RBAC) and data lineage tracking within Microsoft Fabric.• Designing and developing scalable and efficient data warehouse solutions on Azure Synapse, including schema design, data modeling, and ETL processes to support analytical reporting and business intelligence requirements.• Leveraging Azure Synapse for advanced analytics and machine learning initiatives, including predictive modeling, data mining, and pattern recognition, to derive actionable insights and drive data-driven decision-making.• Design, develop, and implement SSIS packages to extract, transform, and load (ETL) data from various sources into target databases.• Unified Data Storage and Processing: Established a robust Lakehouse infrastructure by integrating data lakes and data warehouses on Databricks, improving data accessibility, consistency, and scalability across the organization.
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