DV is the leader in digital performance solutions, helping our advertiser and agency partners verify the quality of their digital campaigns, Optimise to improve performance and Prove that they’re achieving their business outcomes, through unbiased 3rd party data and analytics. DV’s mission is to be the definitive source of transparency and data-driven insights into the quality and effectiveness of digital advertising for the world’s largest brands, agencies, publishers, and digital ad platforms.  Since 2008, DV has helped hundreds of Fortune 500 companies gain the most from their media spend by delivering best-in-class solutions across the digital advertising ecosystem, helping to build a better industry. Learn more at www.doubleverify.com.

We develop advertising analytics systems that measure the exposure and engagement of digital advertisement. We need to write fast, error-resilient, smart code that can deal with many environments including web & mobile.

We stream these large amounts of data through a highly scalable backend system, in which we own the micro streaming applications to process the data and withdraw intelligent insights. Insights are then ingested to a data lake running data pipelines to aggregate and produce higher level insights and benchmarks for clients.

• Design cloud-native solutions using Kafka, Kubernetes, and Databricks.
• Develop in Scala (server-side), TypeScript (client-side/tools), and Python.
• Build CI/CD pipelines for robust cloud delivery.
• Scale big data solutions and maintain high-traffic codebases.
• Own end-to-end service health, including real-time monitoring and alerts.
• Utilize AI coding tools to accelerate all stages of the SDLC.

Who you are

• Proactive ownership and a "getting things done" mindset.
• BSc in Computer Science or equivalent.
• Strong communication skills and CS fundamentals.
• 5+ years experience in JS/TS, Scala, Java, Python, or Go. JS/TS experience - advantage.
• Experience with Docker, Kubernetes, SQL, and cloud (GCP/AWS).
• Proficiency in leveraging AI tools (Cursor,Claude, etc.) as a productivity multiplier
• Our interview process reflects how we work. Candidates are encouraged to use AI tools during technical assessments. We evaluate problem-solving, code quality, and how effectively you leverage modern tooling , not whether you can solve algorithmic puzzles from memory.