Caleb Wood

At Walmart Global Tech, I build scalable Python and Spark ETL pipelines processing more than 5TB of data daily with 99.9% uptime. I integrate PostgreSQL, APIs, and Kafka streams to support real-time and batch analytics.

I've improved reporting data models to reduce query latency by 40%, decreased pipeline incident resolution time by 30%, and increased processing throughput by 25%. I also implement governance, access controls, documentation, and lineage practices that keep datasets secure, reliable, and accessible.

Across my Walmart roles, I've developed ingestion pipelines for MySQL, MongoDB, and external APIs, automated ETL workflows with Airflow, and supported BI reporting in Snowflake and Redshift. I work closely with Product, Analytics, and cloud engineering teams to turn business requirements into durable data solutions.

Earlier, I analyzed sales and inventory data at Superior Automotive Group, building SQL reports and validation processes that improved data accuracy by 15%. I bring seven years of data engineering experience, a Computer Science background, and a focus on clean datasets that empower analytics and BI teams.