Engineering Scalable Data Frameworks: Architected and deployed market-agnostic data validation frameworks using PySpark and SQL within Databricks, ensuring data integrity across Bronze, Silver, and Gold layers for global Marketing Mix Modeling (MMM) initiatives.
Automated Data Quality (ADQ): Engineered and configured a Data Automation Testing Framework (DATF), transforming manual SQL checks into parameter-driven, reusable automated pipelines that accelerated cross-market delivery for 7+ global regions.
CI/CD & DevOps Integration: Integrated automated testing workflows into Azure DevOps (ADO) pipelines, streamlining production-readiness checks and enabling scalable, continuous data integration across complex enterprise datasets.
End-to-End Pipeline Governance: Led the end-to-end technical validation of complex business logic and audit transformations, collaborating with Data Engineers to triage defects and optimize downstream performance for production-grade delivery.
Advanced Data Reconciliation: Developed rigorous scripts for metadata validation, count reconciliation, and duplicate detection, ensuring high-fidelity data consumption for large-scale analytics and enterprise growth domains.