About the team
The mission of Roku's Data Engineering team is to develop a world-class big data platform so that internal and external customers can leverage data to grow their businesses. Data Engineering works closely with business partners and Engineering teams to collect metrics on existing and new initiatives that are critical to business success. As a Senior Data Engineer working on Device metrics, you will design data models & develop scalable data pipelines to capture different business metrics across different Roku Devices.
About the role
Roku pioneered streaming to the TV. We connect users to the streaming content they love, enable content publishers to build and monetize large audiences, and provide advertisers with unique capabilities to engage consumers. Roku streaming players and Roku TV™ models are available worldwide through direct retail sales and licensing arrangements with TV brands and pay-TV operators. With tens of million players sold across many countries, thousands of streaming channels and billions of hours watched over the platform, building scalable, highly available, fault-tolerant, big data platform is critical for our success. This role is based in Bangalore, India, and requires hybrid working, with 4 days in the office.
How will I use AI at Roku?
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 you 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.
What you'll be doing
- Build highly scalable, available, fault-tolerant distributed data processing systems (batch and streaming systems) processing over 10s of terabytes of data ingested every day, and a petabyte-sized data warehouse
- Build quality data solutions and refine existing diverse datasets to simplified data models, encouraging self-service
- Build data pipelines that optimize on data quality and are resilient to poor quality data sources
- Own the data mapping, business logic, transformations, and data quality
- Low-level systems debugging, performance measurement & optimization on large production clusters
- Participate in architecture discussions, influence product roadmap, and take ownership and responsibility over new projects
- Maintain and support existing platforms and evolve to newer technology stacks and architectures
We're excited if you have
- Extensive SQL Skills
- Proficiency in at least one scripting language, Python, is required
- Experience in big data technologies like HDFS, YARN, Map-Reduce, Hive, Kafka, Spark, Airflow, Presto, etc.
- Proficiency in data modeling, including designing, implementing, and optimizing conceptual, logical, and physical data models to support scalable and efficient data architectures.
- Experience with AWS, GCP, and Looker is a plus
- Collaborate with cross-functional teams such as developers, analysts, and operations to execute deliverables
- 8+ years of professional experience as a data Engineer
- BS in Computer Science; MS in Computer Science preferred
- AI Literacy / AI growth mindset
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