Josh Johnson
@joshjohnson
Staff Data Engineer focused on building scalable cloud-native data platforms, streaming pipelines, and Customer 360 solutions.
United StatesWhat I'm looking for
I’m a Senior/Staff Data Engineer with 8+ years of experience designing and scaling cloud-native data platforms across SaaS, finance, and analytics. I specialize in the modern data stack and real-time streaming—building reliable systems that turn raw events into trustworthy analytics and ML-ready data.
At Klaviyo, I led development of a Customer 360 Data Platform on AWS, unifying customer identity across 25+ SaaS systems and enabling analytics for 200+ enterprise clients. I built “ChurnIQ” predictive retention pipelines, automated ELT workflows with dbt/Fivetran/Airflow, implemented Reverse ETL to sync Redshift to Salesforce and Braze, and deployed AI-assisted anomaly detection to improve data reliability SLAs by 30%. I also mentor engineers, enforce data quality standards with Great Expectations, and optimize performance and cost in Redshift—bringing latency down from 6 hours to under 15 minutes using Kinesis ingestion.
Experience
Work history, roles, and key accomplishments
Led development of Klaviyo’s Customer 360 Data Platform, unifying customer identity data across 25+ SaaS systems for analytics used by 200+ enterprise clients. Reduced data latency from 6 hours to under 15 minutes via Kinesis streaming ingestion and improved retention insight accuracy by 28%, while automating ELT workflows with dbt, Fivetran, and Airflow to cut manual maintenance by 40%.
Developed and maintained the Flowcode Analytics Pipeline for real-time processing of 400M+ daily QR scan and engagement events using AWS Glue, Kinesis, and Redshift. Improved data freshness from 24 hours to 3 hours with dbt models and automated REST API/CRM ingestion scripts, reducing manual data loads by 70%, while maintaining 99.9%+ data accuracy with Great Expectations and AWS CloudWatch.
Supported the migration of enterprise data assets to the Capital One Data Lake on AWS, helping modernize data infrastructure for analytics scalability. Assisted with ETL workflows for the DataHub metadata platform using PySpark and AWS Glue, and wrote SQL validation scripts to test data accuracy, troubleshoot ingestion issues, and support GDPR and SOX-aligned reporting.
Education
Degrees, certifications, and relevant coursework
University of Washington
Bachelor of Science, Computer Science
2015 - 2018
Earned a Bachelor’s degree in Computer Science at the University of Washington from 2015 to 2018.
Availability
Location
United StatesAuthorized to work in
Job categories
Skills
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