Matt Tanous

Designed a unified metrics layer with dbt and DuckDB and built ELT pipelines into BigQuery, reducing manual reporting by 60% and increasing onboarding throughput by 25% through automated verification and AI-assisted documentation.

Architected Spark ETL on OCI to migrate billions of rows to Autonomous Data Warehouse and built event-driven Kafka→Snowflake ingestion, improving debugging time by 40% and enabling real-time telemetry features.

Built usage metering and event-modeling pipelines with dbt and Snowflake to support per-seat billing and retention analytics, and automated metadata ingestion across 300+ datasets to improve discoverability.

Delivered product and store performance Tableau dashboards and automated SKU refreshes, cutting manual effort by 70% and consolidating legacy workflows to reduce report duplication by 40%.

Contributed to data warehousing for the SenseAware IoT platform and built Tableau dashboards and SQL Server procedures to monitor SLAs and visualize delivery patterns, improving route efficiency through modeling.

Completed a degree in Computer Engineering with coursework covering hardware and software foundations, embedded systems, and computer architecture.