About the Role:
This is not a traditional QA role.
Data Test Engineering (DTE) validates analytics and data pipelines end-to-end — from events
generated across streaming clients through ingestion, transformation, data warehouses, and downstream
reporting.
We are looking for a hands-on Data Test Engineer who combines data validation, automation
engineering, and strong troubleshooting skills to protect data quality at streaming scale.
What You’ll Do:
● Validate analytics events across Web, iOS, Android, tvOS, Roku, Fire TV, and other connected
TV platforms.
● Validate data end-to-end across ingestion, transformation, and reporting layers using SQL and
data profiling to verify transformations, identify anomalies, and troubleshoot data-quality issues,
including validation in BigQuery.
● Build and maintain Java/Spring-based automation for scalable back-end and pipeline
validation.
● Expand automated regression coverage within DTE and shared GQE automation frameworks.
● Create and use Claude Skills and AI-assisted tools such as Claude and Cursor to improve
validation, test development, troubleshooting, and engineering productivity.
● Develop test strategies and partner with BI, Data Architecture, AIDE, Product, and Engineering to
drive issues through resolution.
● Support production validation, platform rollouts, traffic ramps, and post-launch data monitoring.
Qualifications:
● 5+ years of QA, Test Engineering, Data Quality Engineering, or related experience, with 3+ years
focused on data pipelines, warehousing, or analytics validation.
● Strong SQL skills and hands-on experience with BigQuery or similar cloud data warehouses.
● Strong understanding of end-to-end data pipelines, from event generation and ingestion
through transformation and reporting.
● Java development experience, preferably with Spring/Spring Boot, for automation frameworks
or back-end validation.
● Experience building or contributing to automated test/data-validation frameworks.
● Experience validating analytics implementations across web, mobile, OTT, or connected TV
platforms.
● Experience with Python or shell scripting and cloud/data platforms such as GCP/AWS,
Airflow/Cloud Composer, and MongoDB Atlas; exposure to Jenkins/GitHub Actions,
Tableau/Mode, Tealium, or Redshift is a plus.
● Experience with AI-assisted development or testing, using tools such as Claude, Cursor,
Claude Skills, AI agents, or other LLM-based workflows, is a plus.
● Strong debugging, problem-solving, and communication skills in an Agile engineering
environment.