Senior Data Engineer

Roku•San Jose, CA

2d•$148,750 - $361,000•Hybrid

About The Position

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. As a Senior Data Engineer on the Viewer Product Data Engineering team, you will play a pivotal role in designing data models and building scalable pipelines to capture business metrics across Roku devices, Roku-powered TVs, web, and mobile clients. Your work will enable data-driven decisions that shape the content discovery and viewing experience for millions of users worldwide. You will build and maintain highly scalable, fault-tolerant distributed data processing systems that handle tens of terabytes of data ingested daily and a petabyte-scale data warehouse. By delivering trusted, high-quality data products, you will help teams understand which product features resonate most with users, measure their impact, and uncover opportunities to continuously improve the Roku experience. You will also participate in architecture discussions, influence the product roadmap, and take ownership of new projects from inception to delivery. This is an exciting opportunity for a data engineering professional who thrives in a fast-paced environment and is passionate about solving complex data challenges at scale. At Roku, we don't just use AI, we work with it. AI agents and smart tools help power drafts, analysis, and repetitive workflows, while our people bring direction, judgment, and accountability. We're looking for curious, adaptable builders who can show how they've used AI or automation to move faster, raise the bar, and scale their impact. We value your AI skills if have built fluency across the agentic engineering toolchain — coding harnesses like Claude Code or Cursor, MCP servers, custom skills, or agent frameworks. And you can describe projects where you shipped real work with these tools. You know how to drive an agent, verify its output, and ramp on an unfamiliar codebase with an agent helping you.

Requirements

8+ years of professional experience as a Data Engineer
Extensive SQL skills with the ability to write complex, optimized queries
Proficiency in at least one scripting language, with Python preferred
Extensive experience with big data technologies such as Hadoop (HDFS, YARN, MapReduce), Hive, Kafka, Spark, Airflow, and Presto/Trino
Deep expertise in Apache Spark, including performance tuning, optimization, and building scalable batch and streaming data pipelines
Proficiency in data modeling, including designing, implementing, and optimizing conceptual, logical, and physical data models to support scalable and efficient data architectures
Experience collaborating with cross-functional teams such as developers, analysts, and operations to deliver results
BS in Computer Science or a related field; MS in Computer Science preferred
AI literacy and an AI growth mindset

Nice To Haves

Experience with AWS, GCP, or Looker

Responsibilities

Build highly scalable, available, and fault-tolerant distributed data processing systems (batch and streaming) that process tens of terabytes of data daily and manage a petabyte-scale data warehouse
Design and build quality data solutions and refine diverse datasets into simplified data models that encourage self-service analytics
Develop data pipelines that optimize for data quality and are resilient to poor-quality data sources
Own data mapping, business logic, transformations, and data quality standards
Perform low-level systems debugging, performance measurement, and optimization on large production clusters
Participate in architecture discussions, influence the product roadmap, and take ownership and responsibility for new projects
Maintain and support existing platforms and drive evolution to newer technology stacks and architectures