At a Glance
- Tasks: Build and maintain data pipelines for Roku's CTV advertising auction platform.
- Company: Join Roku, the leading TV streaming platform transforming how the world watches TV.
- Benefits: Enjoy flexible work options, comprehensive health benefits, and support for mental wellness.
- Other info: Collaborative hybrid work environment with opportunities for personal and professional growth.
- Why this job: Make a real impact in the fast-paced world of advertising technology.
- Qualifications: Experience with data pipelines, SQL, Python, and cloud platforms is a plus.
The predicted salary is between 60000 - 80000 £ per year.
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. 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.
About the Team: 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 real-time 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.
About the Role: 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.
What You'll Be Doing:
- 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.
We're Excited If You Have:
- 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.
Our Hybrid Work Approach: Roku fosters an inclusive and collaborative environment where teams work in the office Monday through Thursday. Fridays are flexible for remote work except for employees whose roles are required to be in the office five days a week or employees who are in offices with a five-day in-office policy.
Benefits: Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Employees are supported in taking time off, in accordance with local leave policies and other personal needs to support their evolving work and life needs.
Accommodations: Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to EmployeeRelations@Roku.com.
Data Engineer, Ads Auction Platform employer: Roku, Inc.
Roku is an exceptional employer that champions innovation and collaboration, offering a dynamic work environment where every team member contributes to shaping the future of TV streaming. With a strong focus on employee well-being, Roku provides comprehensive benefits, including mental health support and flexible working arrangements, fostering a culture of inclusivity and growth. As a fast-growing public company, employees have the opportunity to engage in meaningful projects that impact millions of viewers while developing their skills in a cutting-edge technological landscape.
