HexaCorp developed the Data Foundation Data Ingestion Framework, a comprehensive solution designed to extract and ingest data from diverse sources using a Self-Service UI Portal. The framework is built on a metadata-driven approach to simplify data engineering processes, reduce development time, and minimize maintenance efforts.

• Encountered significant hurdles in configuring diverse Azure resources and ensuring seamless data governance across various layers.
• Data Source Complexity: Managing multiple Azure services such as: Azure Data Factory (Orchestration and Acquisition), Azure Databricks and Delta Lake, Azure Data Lake Storage, Azure SQL Server, Key Vault, Logic Apps, Function Apps, Azure Service Bus, Event Grid, and Log Analytics.
• Aligning data governance with team-specific roles to provide tailored permissions.
• Managing schema evolution and incremental data loads across growing datasets.
• Implementing Unity Catalog for metadata management and compliance across multiple workspaces.

• Designed a metadata-driven ingestion framework, enabling the configuration of pipelines and data assets via a user-friendly Self-Service UI Portal.
• Integrated advanced error-handling, audit, and monitoring mechanisms to reduce downtime and manual interventions.
• Leveraged Azure Data Factory for orchestrating data pipelines and enabling seamless integration with other Azure services.
• Implemented Azure Databricks and Delta Lake for high-performance data processing and transactional consistency.
• Utilized Azure Data Lake Storage for scalable and secure data storage with optimized read/write performance.
• Secured sensitive configurations via Azure Key Vault, ensuring centralized and secure secret management.
• Automated workflows using Azure Logic Apps and Function Apps to enhance efficiency.
• Employed Azure Service Bus and Event Grid for reliable communication and orchestration between services.
• Configured Azure Log Analytics for centralized logging, monitoring, and diagnostics.
• Established a Unity Catalogue for centralized metadata and role-based access control(RBAC) to ensure secure, compliant data management.
• Designed granular access controls aligned with team roles to improve governance and security.
• Implemented data lineage and compliance tracking features to facilitate auditing and secure data sharing.
• Automated pipeline instantiation to significantly reduce development and deployment time.
• Designed a robust architecture for managing schema evolution and incremental data loads, minimizing maintenance overhead.
• Established a scalable framework to support the seamless integration of new data sources without impacting existing processes.