Senior Data Test Engineer

Paramount creates entertainment experiences that drive conversation and culture around the world. Through television, film, digital media, live events, merchandise and solutions, our brands connect with diverse, young and the young at heart audiences in more than 180 countries.

Pluto TV , a Paramount company, is the leading free streaming television service in America, delivering 250+ live and original channels and thousands of on-demand movies in partnership with major TV networks, movie studios, publishers, and digital media companies. Pluto TV is available on all major mobile, web, and connected TV streaming devices and millions of viewers tune in each month to watch premium news, TV shows, movies, sports, lifestyle and trending digital series. Headquartered in West Hollywood, Pluto TV has offices in New York, Silicon Valley, Chicago, and Berlin. We have team members located all over the globe.

We are a leading streaming platform delivering live and on-demand content to millions of users globally across web, mobile, and connected TV platforms. The Data Test Engineering (DTE) team protects the quality and integrity of analytics and data pipelines end-to-end — from analytics events generated on client applications through ingestion, transformation, data warehouses, and downstream reporting.

• Interview process that respects people and their time
• Professional and open IT community
• Internal meet-ups and resources for knowledge sharing
• Time for recovery and relaxation
• Bright online and offline events
• Opportunity to become part of our internal volunteer community

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.

• 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.

  What Sets You Apart

• You think like an engineer, not just a tester.

• You can move between client analytics, back-end pipelines, warehouses, and automation

• code.

• You build reusable automation instead of relying on repetitive manual validation.

• You take ownership of complex data-quality issues and drive them end-to-end.

• You are interested in applying AI to improve data quality engineering.