Google Data Architect

Architected and delivered a comprehensive retail media network solution that transformed how enterprise clients optimize advertising spend across multiple channels. This strategic initiative integrated Google Ad Manager and Criteo platforms, creating a unified data ecosystem that processes feeds from diverse channel partners while maintaining real-time performance analytics.

Business Impact & Results

• Revenue Optimization: Implemented sophisticated attribution modeling that increased advertising ROI by 40% through precise cross-channel performance measurement
• Operational Efficiency: Automated data consolidation reduced manual reporting time by 75%, enabling marketing teams to focus on strategic optimization
• Data-Driven Decision Making: Created comprehensive analytics dashboards that empowered stakeholders with real-time insights into CTR, CPC, CPM, and conversion metrics
• Scalable Architecture: Built platform capable of processing millions of advertising events daily with sub-second latency requirements

Strategic Solution Architecture

Designed a cloud-native data platform leveraging Google Cloud's enterprise-grade services to create a scalable, resilient advertising analytics ecosystem. The solution integrated multiple third-party APIs while maintaining strict data quality standards and implementing comprehensive monitoring frameworks.

Technical Excellence & Innovation

Leveraged BigQuery's advanced analytical capabilities coupled with Google Composer for sophisticated workflow orchestration. Implemented event-driven processing automation using Cloud Functions and established robust CI/CD pipelines that enabled rapid iteration and deployment of new features while maintaining system reliability.

Technology Stack

Led the strategic modernization of enterprise data infrastructure, architecting a next-generation data warehouse solution optimized for high-performance OLAP operations. This transformative initiative established advanced ETL frameworks, implemented performance tuning strategies, and created automated workflow orchestration capabilities that positioned the organization for scalable analytical growth.

Strategic Business Outcomes

• Performance Excellence: Achieved 10x improvement in query performance through optimized BigQuery architecture and advanced partitioning strategies
• Operational Scalability: Enabled self-service analytics capabilities for business users, reducing IT dependency by 60%
• Data Governance: Implemented comprehensive data quality frameworks with automated validation processes, improving data accuracy by 95%
• Cost Optimization: Reduced infrastructure costs by 45% while significantly expanding analytical capabilities and processing capacity

Architecture & Design Excellence

Engineered a modern data warehouse leveraging Google Cloud Platform's enterprise services, implementing sophisticated ETL frameworks that seamlessly integrate multi-source data while maintaining strict performance and quality standards. The solution incorporates advanced slowly changing dimension (SCD) types 1, 2, and 3 to support diverse analytical use cases.

Technical Innovation & Implementation

Developed comprehensive Python and SQL-based data processing frameworks that automate complex data transformations and orchestrate workflows through Google Cloud Composer. Established robust monitoring and alerting systems using Google Cloud Console and Log Explorer, ensuring optimal system performance and proactive issue resolution.

Technology Stack

Engineered a enterprise-grade Master Data Management solution that revolutionized data quality and consistency across organizational systems. This strategic initiative developed an intelligent address master database with automated cleansing capabilities, USPS validation integration, and golden record creation that established a single source of truth for critical business data.

Transformational Business Impact

• Data Quality Excellence: Achieved 98% data accuracy improvement through automated cleansing and USPS validation, eliminating costly data errors
• Operational Efficiency: Reduced manual data maintenance by 80% through intelligent automation and rule-based processing
• System Integration: Created unified data architecture supporting both real-time applications and analytical reporting with seamless synchronization
• Compliance & Governance: Established comprehensive audit trails and data lineage tracking, ensuring regulatory compliance and data transparency

Strategic Architecture & Design

Implemented a sophisticated dual-storage architecture leveraging BigQuery for analytical workloads and Firestore for real-time applications. This hybrid approach optimized performance across different use cases while maintaining data consistency through automated synchronization processes and comprehensive validation frameworks.

Advanced Technical Implementation

Developed intelligent rule engines using Python that orchestrate complex data flows and transformations. Utilized dbt (data build tool) for robust data modeling, quality validation, and documentation. Implemented automated testing frameworks and CI/CD pipelines using GitHub Actions, ensuring reliable deployments and continuous quality assurance.

Innovation & Process Excellence

Created sophisticated golden record algorithms that intelligently merge and standardize data from multiple sources. Implemented dimensional modeling best practices to support scalable analytical capabilities while maintaining flexibility for evolving business requirements.

Technology Stack

Orchestrated comprehensive enterprise cloud transformation initiatives that modernized legacy data infrastructure through strategic migrations from multiple platforms including Teradata, SQL Server, SAS, and Oracle Exadata to Google BigQuery. This enterprise-scale project involved architecting migration solutions, converting 2,000+ legacy code segments, and implementing robust three-tier architectures while ensuring zero-downtime transitions and maintaining data integrity across petabytes of historical business data.

Strategic Business Transformation

• Comprehensive Modernization: Successfully migrated from multiple legacy platforms (Teradata, SQL Server, SAS, Exadata) to unified BigQuery ecosystem
• Code Transformation: Converted 2,000+ SAS code segments to BigQuery SQL while maintaining complete data integrity and business logic
• Performance Excellence: Achieved 15x improvement in query performance through advanced BigQuery optimization and intelligent partitioning strategies
• Cost Optimization: Reduced infrastructure costs by 65-70% while dramatically improving scalability and advanced analytics capabilities
• Business Continuity: Executed zero-downtime migrations ensuring uninterrupted business operations throughout transformation processes

Migration Strategy & Architecture Excellence

Developed and executed comprehensive migration strategies leveraging BigQuery Data Transfer Service and advanced orchestration workflows. Engineered sophisticated three-tier architecture encompassing Data Acquisition Layer for seamless data ingestion, EDW Data Layer for advanced processing and transformation, and Semantic Layer for structured data access and reporting. This design ensured scalable, maintainable data processing workflows supporting diverse analytical use cases.

Technical Excellence & Quality Assurance

Implemented rigorous data validation processes through comparative analysis between source and target systems, ensuring complete data accuracy throughout migration lifecycles. Developed comprehensive testing frameworks to validate code conversion accuracy and established automated processes for ongoing maintenance and optimization. Created custom Python and SQL scripts for data transformation and developed event-driven automation using Google Cloud Functions.

Performance Optimization & Monitoring

Implemented advanced BigQuery optimization techniques including strategic partitioning, clustering, and query optimization. Established comprehensive monitoring and management frameworks using Google Cloud Console and Log Explorer, ensuring optimal system performance and proactive issue resolution. Created business-critical metrics and views optimized for integration with modern reporting tools.

Technology Stack