Prathyusha D.

Led the Azure data engineering workstream for a major Canadian banking client, delivering cloud-native ETL pipelines, Medallion Architecture data lakehouses, and enterprise Power BI reporting to 200+ business users. Designed Azure Data Factory pipelines for batch and real-time ingestion from SQL Server, Snowflake, and Azure Data Lake Gen2 Migrated 20+ legacy SSRS reports to Power BI — reducing report maintenance overhead by 30% and data refresh time by 40% Embedded OSFI and PIPEDA compliance controls into the ADF pipeline layer — achieved 100% compliance pass rate with zero exceptions Built Medallion Architecture (Bronze/Silver/Gold) in Azure Databricks with Delta Lake, consumed by Power BI Fabric Semantic Models Integrated Azure Purview with Azure Sentinel for end-to-end data lineage and real-time security monitoring Designed CI/CD pipelines in Azure DevOps — reduced release cycle by 30% Used Claude AI, Cursor, and Microsoft Copilot daily — reducing repetitive development effort by ~25% Contract concluded February 2026. Currently completing PL-300 and DP-700 certifications while actively seeking the next opportunity in Canada.

Built Azure-native data pipelines and Power BI reporting platforms for live infrastructure project sites across India. • Built ADF pipelines ingesting construction project data into Azure Data Lake Gen2 — reduced manual reporting effort by 35% and delivered daily operational visibility that had previously been one week behind schedule Consolidated three siloed data systems into a single unified reporting layer — resolved data conflicts and established a trusted single source of truth for project management teams • Migrated legacy SSIS workloads to Azure Data Factory— reduced Azure Blob Storage costs by 25% • Built Power BI dashboards tracking real-time KPIs (cost variance, resource utilisation, milestone progress) — cut dashboard load time by 35% through DAX and data model optimisation • Implemented data replication in Azure Databricks (Delta Lake) and column-level data masking in Snowflake for enterprise data security • Developed data governance frameworks for Azure Data Lake — schema standards, metadata structures, and stewardship policies.

Delivered enterprise BI and ETL solutions for one of India's largest private sector banks, serving 150+ financial analysts across investment, retail, and commercial banking. Migrated 100+ legacy on-premise reports and OLAP cubes to Power BI and Report Builder — enabled self-service analytics for 150+ financial analysts, reduced IT dependency by 40%, and cut report delivery time from days to hours Rebuilt RBI regulatory reporting in SSRS with embedded data validation and reconciliation checks — replaced a manual, error-prone process and achieved a 100% audit pass rate across all subsequent regulatory submissions Diagnosed and resolved severely underperforming SQL queries across large-scale banking transaction datasets — redesigned query logic and rebuilt indexing strategies, improving execution time by 50% Designed ETL pipelines using SSIS and Azure Data Factory to extract, transform, and load financial data from core banking systems into the data warehouse and dimensional models Built SSAS OLAP cubes for multidimensional financial analysis — defined metrics, dimensions, and KPIs with business analysts Configured Azure Data Factory linked services with Managed Identity authentication and Azure Synapse firewall rules for secure, credential-free data access Collaborated with compliance teams on data archiving and retention policies aligned with RBI regulatory requirements