<p>Contributed to the Lift & Shift modernization initiative by migrating legacy applications and data workloads to scalable modern platforms.</p><p> Designed and created 70+ Oracle database tables to support high-volume transaction processing, reporting, and reconciliation requirements.</p><p> Migrated and modernized 15+ Oracle batch processes for data ingestion, transformation, validation, and downstream reporting.</p><p> Developed PL/SQL scripts to support historical data migration, backloading, and reconciliation activities.</p><p> Backloaded 3–5 years of historical transaction data while ensuring data completeness, accuracy, and consistency across systems.</p><p> Performed Oracle query tuning, batch performance optimization, and large-scale data migration activities to improve processing efficiency.</p><p> Designed and developed an end-to-end Apache NiFi pipeline with MiniO, Spark, HDFS, API for regulatory reporting requirements, incorporating dependency-based workflow orchestration, secure encryption/decryption processing, automated validations, exception handling, and monitoring controls to support reliable daily production operations and compliance-driven reporting.</p><p> Delivered enhancements across Spark, NiFi, HDFS, MinIO, and API integration layers to improve pipeline reliability and maintainability.</p><p> Built automation solutions for audit controls, reconciliation validation, data quality checks, and operational efficiency improvements.</p><p> Contributed to platform migration and modernization initiatives involving Apache Airflow and Cloudera Data Engineering.</p><p> Led production deployments, validations, and release activities across multiple environments in alignment with enterprise change and release management processes.</p><p> Collaborated with business stakeholders, architects, support teams, and external partners to deliver regulatory compliance-driven data solutions.</p><p> Performed issue analysis, root-cause investigation, and production incident resolution to ensure platform stability and timely regulatory reporting.</p><p> Developed PySpark-based solutions for large-volume data processing, transformation, and validation workloads.</p><p> Designed Splunk-based monitoring, alerting, and operational dashboards to improve pipeline observability and supportability.</p><p> Implemented frameworks for retention management, purge automation, audit validation, and data quality monitoring.</p><p> Designed proactive threshold-based monitoring and alerting mechanisms to identify issues early and improve operational resilience.</p>
