Senior Data Engineer

Roku · Bengaluru

  • Experience7–11 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelexecutive
  • Posted2 Sept 2026
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About Roku

Roku is hiring in Bengaluru in media advertising. This role looks for around 7+ years of experience.

Skills

  • SQL
  • Python
  • Hadoop
  • HDFS
  • YARN
  • MapReduce
  • Hive
  • Kafka
  • Apache Spark
  • Airflow
  • Presto
  • Trino
  • Data Modeling

The role

A data engineer at a streaming media company builds scalable batch and streaming data pipelines with Apache Spark and Kafka, shapes distributed data processing systems and data models, and optimizes production clusters with SQL and Python.

Full job description

As a Senior Data Engineer on Roku's content data engineering team, you'll play a critical role in shaping how Roku understands and improves the content experience for millions of users worldwide. Our team builds the foundational data products, scalable pipelines, and analytics models that power decision-making across Roku's content ecosystem.

Responsibilities:

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 into simplified data models, encouraging self-service.

Build data pipelines that optimize for 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, 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 evolve to newer technology stacks and architectures.

Requirements:

Extensive SQL Skills.

Proficiency in at least one scripting language; Python is 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 is required, 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 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.