Data Engineer, Ads Auction Platform

Teamwork makes the stream work.
Roku is changing how the world watches TV

Roku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers.

From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines.

The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem - Advertisers, Publishers and Roku. The systems and solutions span across different disciplines and technologies to perform realtime multi-objective optimization with distributed systems at large scale and low latencies. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems and Auction Dynamics to solve a large set of complex problems.

At the core of this is our Machine Learning, Experimentation and Inference Platform that powers the entire landscape which we continuously evolve over time.

In this role, you will build and maintain data pipelines and analytics infrastructure that power Roku’s CTV advertising auction platform. You will support marketplace optimization by delivering high-quality datasets for advertiser performance, publisher yield, and revenue analysis across batch and near real‑time workflows. You will partner with product, analytics, and data science teams to translate business needs into well‑modeled, reliable data products.

You will contribute to experimentation, simulation, and reporting foundations that inform bidding strategy and monetization decisions. This role is ideal for an engineer who enjoys high‑scale data systems, strong data quality practices, and measurable business impact.

• Design and maintain data pipelines and analytics infrastructure supporting Roku’s CTV advertising auction platform
• Build ETL/ELT workflows in Airflow to process auction events including delivery, bids, impressions, pricing, budget usage, and frequency cap signals
• Create scalable batch and streaming pipelines for billions of daily ad events with strong freshness, accuracy, and schema consistency
• Model datasets for multi‑objective optimization and marketplace analytics across advertiser, publisher, and platform outcomes
• Design aggregated tables and materialized views to support closed‑loop analysis of auction results and bidding behavior
• Own integrations from DSPs, programmatic exchanges, and direct campaigns and standardize schemas for unified reporting
• Partner with data scientists, analysts, and product teams to deliver clean, discoverable, and trusted datasets
• Enable yield and gross profit analysis through dimensional models, win‑rate metrics, demand health indicators, and experiment measurement tables
• Build data foundations for A/B testing analysis, auction simulation, offline replay, and post‑campaign reporting
• Implement data quality checks, monitoring, and observability while supporting privacy and governance requirements

• Experience designing and operating production data pipelines at scale
• Strong SQL and Python skills and hands‑on Airflow experience
• Experience with both batch and streaming data architectures
• Familiarity with cloud data platforms and distributed processing systems
• Experience modeling event‑driven data for analytics and experimentation
• Knowledge of ad tech data concepts such as auctions, bids, pacing, and yield
• Strong fundamentals in data quality, lineage, monitoring, and governance
• Ability to partner effectively with cross‑functional technical and business teams

Roku fosters an inclusive and collaborative environment where teams work in the office Monday through…