Work - Production Systems That Actually Scale

I implemented a GDPR-compliant analytics solution for a European luxury fashion brand handling sensitive ultra-high-net-worth client data across 8 EU jurisdictions.

The solution leveraged policy tags, OpenMetadata for data lineage, and DBT anonymization techniques to achieve comprehensive auditability in 3 weeks.

The project established comprehensive data governance with automated compliance monitoring, data anonymization, and complete audit trails for regulatory requirements.

I implemented a comprehensive real-time fraud detection solution for a Series B payment processing startup handling 10M transactions per day.

The solution leveraged Terraform, Kafka, DBT, and Cube.js to achieve 1.5-second latency and 15% fraud reduction while reducing false positives by 68%.

The project established a scalable fraud detection platform supporting real-time transaction monitoring with automated alerting, overcoming challenges in false positive tuning.

I implemented a data mesh architecture to unify 200+ data sources for a multi-national retail chain operating across 12 countries.

The solution leveraged domain-driven design and modern data stack technologies to achieve 75% faster data access and 58% reduction in data silos.

The project established a scalable, decentralized data architecture supporting real-time analytics and operational reporting across retail domains, despite initial team resistance to decentralization.

I implemented a comprehensive MLOps solution for a national retail chain with 500+ locations, enabling automated anomaly detection across sales, inventory, and customer behavior.

The solution leveraged DBT for feature engineering and Airflow for orchestration, achieving 38% faster ML deployment and 93% accuracy in anomaly detection after several tuning iterations.

The project established a scalable, automated ML pipeline supporting real-time anomaly detection with continuous model improvement, overcoming initial accuracy challenges.

Designed and implemented a cost-optimized real-time streaming architecture processing 300M events per day for a rapidly-growing e-commerce platform.

The solution leveraged Kafka, DBT, and Cube.js to achieve 1.8-second latency and 27% cost reduction through intelligent resource allocation.

The project established a scalable, high-performance streaming platform supporting real-time analytics and operational monitoring, overcoming initial Kafka tuning challenges.

I successfully migrated an online betting platform's 5TB MySQL database to cloud-native architecture with only 3 minutes of downtime.

The solution leveraged Debezium CDC, Airbyte, DBT, and BigQuery to achieve minimal data loss (< 0.01%) and 99.7% uptime during the 3-week migration.

The project established a scalable, cloud-native data platform supporting real-time analytics and operational reporting with 48% improved query performance.

I implemented a comprehensive multi-cloud governance solution for a regional financial services firm managing AWS/GCP hybrid infrastructure across 200+ resources.

The solution leveraged Terraform, OpenMetadata, and automated governance tools to achieve 35% cost reduction and 96% compliance automation.

The project established a scalable, multi-cloud governance framework supporting automated compliance, cost optimization, and security enforcement across hybrid environments.

I implemented a self-service BI solution for a Fortune 500 consumer goods conglomerate, eliminating IT bottlenecks and empowering 500+ business users with direct data access.

The solution leveraged modern data stack technologies to achieve 72% faster report generation and 58% reduction in IT support requests.

The project established a scalable, user-friendly BI platform with comprehensive training programs that overcame initial user adoption challenges to reach 92% user satisfaction.