What you'll be doing

• Lead technical architecture, design, and development of enterprise data quality, discovery, and governance frameworks.
• Establish and enforce enterprise-wide data governance standards, policies, tooling, and processes to ensure accurate, compliant, and discoverable data assets across Roku.
• Lead design and implementation of custom integrations within data discovery frameworks like Datahub for metadata-driven lineage and search.
• Develop AI/ML-based solutions for data quality, anomaly detection, and automated data discovery.
• Extend and customize open-source data quality frameworks and tools like Deequ and Great Expectations to ensure quality across critical datasets.
• Design and implement robust batch and real-time data pipelines using Apache Spark to support large-scale daily data volumes exceeding 10TB and real-time pipelines processing millions of events per minute.
• Build and maintain enterprise data warehouses and data solutions in AWS/GCP cloud environments using big data technologies, ensuring operational stability and optimal performance at petabyte scale.
• Design and develop cloud-agnostic tooling, CI/CD pipelines, serverless compute, and containerized deployments with Kubernetes.
• Provide technical leadership by mentoring and directing engineers and consultants, driving roadmap and sprint planning, and defining long-term strategies for data quality and governance initiatives.
• Collaborate with product managers, data analysts, data scientists, ML engineers, backend engineers, and business stakeholders to translate requirements into scalable data models and data solutions, improve event logging frameworks, enforce data governance standards, and strengthen data foundations for enterprise-wide adoption.
• Influence enterprise-wide technical direction, lead cross-functional efforts to unify fragmented governance practices, drive build-versus-buy decisions, define data asset prioritization frameworks for governance investment, and establish long-term strategies for data engineering, quality, and governance.

You are required to have

• Master's degree or foreign equivalent in Data Science, Computer Science, or related field.
• 6 years of experience in the position or a related occupation.
• Will also accept a Bachelor's degree or foreign equivalent in Data Science, Computer Science, or related field and 8 years of progressive experience in the position or a related occupation.

Must have at least 1 year of prior work experience in the following:

1. Technical lead, driving architecture decisions, setting best practices, and guiding teams on data engineering and data governance initiatives in large-scale, consumer-facing digital companies.
2. Design and implementation of enterprise-grade data quality, discovery, and governance frameworks and tools from scratch.
3. Developing Artificial Intelligence (AI) and Machine Learning (ML) solutions to solve data quality, anomaly detection, and data discovery problems.
4. Leading cross-functional projects, partnering with engineering, product, analytics, and data science teams to deliver enterprise-wide data quality and governance solutions, ensuring successful rollout and adoption across the organization.
5. Collaborating with software engineering teams to improve event logging, enforce quality at the source, and manage complex logging frameworks.
6. Managing and mentoring global engineering teams and consultants day-to-day, including roadmap and sprint planning, and driving product roadmap priorities for data governance initiatives.
7. Data discovery platform like Datahub, including developing custom integrations and data quality frameworks like Deequ or Great Expectations.

Must have at least 5 years of prior work experience in the following:

1. Data Modeling, SQL, Airflow, Python, and Java/Scala (including Spark UDFs) and Big Data technologies Spark, HDFS, YARN, Hive, Kafka, Flink, Elastic Search, Grafana and Presto.
2. Developing and optimizing distributed data pipelines using Apache Spark (including Spark on Kubernetes), supporting 10TB+ daily data volume and real-time pipelines processing millions of events per minute.
3. System design and implementation of multi-tier, highly scalable, distributed data pipelines and data warehouses in AWS or GCP cloud environment and cloud-agnostic tooling, CI/CD pipelines, serverless compute, and containerized deployments using Kubernetes.

Up to one day per week telecommuting may be permitted.
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What's Roku's approach to hybrid working?

Roku fosters an inclusive and collaborative environment where teams generally work in the office Monday through Thursday. Fridays are generally flexible for remote work, except for employees whose specific roles or assigned office location require five days' a week attendance.

What are some of the 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. It's important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter.

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 [redacted].