Senior Data Test Engineer

Our Customer 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. The service is available on all 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, the company has offices in New York, Silicon Valley, Chicago, and Berlin.

The company 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 young-at-heart audiences in more than 180 countries.

We are looking for a highly skilled Software Engineer with strong full-stack experience, expertise in distributed systems, and an understanding of product analytics tools to join our engineering team. You will design, build, and integrate with cloud platforms and support business-critical applications.

This role also involves working with Node.js services, CI/CD pipelines, and modern infrastructure tooling, including Kubernetes, GitHub Actions, AWS, and GCP.

• 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.