As a Data Engineer specializing in Data Engineering, Data Warehousing, and ETL, I build and optimize data solutions that drive impactful business decisions. With expertise in tools like Google Cloud Storage, BigQuery, SQL, Python, Databricks, Azure Data Stack, Google Airflow, Microsoft Fabric, Power BI, DBT, and VM management. I design, implement, and manage efficient ETL pipelines that support seamless data orchestration and transformation across platforms. In my role, I: • Architect and manage complex ETL workflows, data trains, and metadata-driven automation to efficiently aggregate, transform, and validate high-quality data across multiple levels. • Develop and implement robust data validation checks, including row count, column integrity, schema validation, referential integrity, business rule adherence, and duplicate detection to ensure data accuracy and completeness. • Optimize and monitor data egress, data extraction, and downstream publishing processes while ensuring cost efficiency, security, and seamless data availability. • Perform and automate system health and performance testing, including batch workflow optimization, ETL job duration analysis, and anomaly detection through outlier analysis, drift analysis, and format validation. • Implement and manage data recovery, backup, and disaster recovery strategies using tools like the Data Recovery Tool (DRT), GCP bucket synchronization, and environment setup for resilience and availability. • Collaborate and align with cross-functional teams to translate business requirements into scalable data solutions, automating notifications and minimizing manual intervention for data readiness. • Execute and enforce data governance best practices by continuously monitoring data quality, running count checks, error log reviews, and validating attributes to maintain a reliable data ecosystem. Skilled in both technical implementation and business alignment, I’m passionate about driving efficiency and reliability in data operations to empower better decision-making across the organization.