Staff Software Engineer

About the role

Staff Software Engineer, TVision Measurement Platform

Viant Technology (NASDAQ: DSP) is investing in AI-powered, identity-driven advertising across CTV and the open internet. TVision is central to this effort, providing next-generation audience measurement through person-level viewing insights. We combine computer vision, audio content recognition, network traffic analysis, and large-scale behavioral data to measure what consumers watch, engagement patterns, and advertising performance across streaming and television environments. This role focuses on designing and operating the distributed systems and data infrastructure that power our measurement platform. You will own durable backend services from intake through deployment, translating raw viewing telemetry into reliable pipelines using Python and modern data tools. The ideal candidate thrives in distributed systems and cares deeply about production outcomes.

Key facts

What you'll do

• Architect ingestion paths for device telemetry that preserve content recognition accuracy and timeliness across measurement pipelines.
• Scale streaming data flows to process billions of seconds of content and audience signals while maintaining strict reliability and latency targets.
• Partner with data science teams to refine computational workflows, driving measurable gains in processing efficiency and analytical precision.
• Design and operate backend services that transform raw viewing telemetry into trustworthy datasets from intake through production deployment.
• Champion operational rigor by implementing robust testing, code review, and monitoring practices that safeguard data delivery integrity.
• Orchestrate infrastructure on AWS using containers and CI/CD patterns to support highly resilient and observable services.
• Shape analytical libraries and data tools alongside data teams to ensure backend workflows remain clear, performant, and well-understood.
• Collaborate with platform teams to ensure TVision tools integrate cleanly within broader measurement ecosystems and third-party workflows.
• Guide product teams by converting viewing insights into actionable signals that inform CTV advertising decisions and strategic optimizations.
• Explore and adopt emerging data platforms and processing frameworks, including big data tools like Spark, Databricks, and Flink where appropriate.
• Define and maintain data lake and warehouse structures using SQL and NoSQL technologies to support fast, accurate measurement queries.
• Automate deployment and operations for containerized services using Kubernetes and modern Git-based workflows to reduce manual toil.
• Monitor system health and performance metrics to detect anomalies, drive reliability improvements, and support rapid incident response.
• Document architectural decisions and operational runbooks to enable scalable knowledge sharing across engineering and product teams.

Requirements

• Hold a Bachelor's degree in a quantitative field such as computer science, engineering, mathematics, or a related discipline.
• Bring 8+ years of hands-on experience building backend services and distributed data systems that operate in production at scale.
• Write Python code following modern engineering practices, including clean abstractions, testing, and maintainable design.
• Have built batch and streaming data pipelines capable of handling large-scale, high-throughput workloads with strict correctness requirements.
• Operate comfortably inside AWS infrastructure, leveraging core services, networking primitives, and security best practices.
• Manage cloud-hosted, containerized web services using orchestration platforms and deployment pipelines that emphasize resilience and repeatability.
• Maintain deep knowledge of relational databases, data lake architectures, and optimization techniques for analytical and transactional workloads.
• Work with big data frameworks such as Spark, Databricks, Flink, or similar technologies to process and aggregate massive viewing datasets.
• Demonstrate strong ownership of production systems, including proactive monitoring, debugging, and performance tuning under real-world load.
• Collaborate effectively with engineers, data scientists, and product managers, communicating tradeoffs clearly and aligning on shared goals.
• Commit to writing inclusive, accessible code and documentation that respects diverse perspectives and supports broad adoption.
• Adhere to security, privacy, and compliance standards relevant to advertising and audience measurement data.
• Show evidence of learning from incidents, conducting blameless postmortems, and driving improvements to reliability and process.
• Engage in code reviews, design discussions, and knowledge-sharing activities that elevate the overall quality of the codebase.

Nice to have

• Experience collaborating with quantitative and data science teams on complex analytical problems in advertising or measurement domains.