Roku

Streaming hardware and ad-supported content

Senior Data Engineer Lead - Data Governance

Data EngineeringConfirmed live in the last 24 hours

Full-timeAustin, TX, USANo salary listed

About the Job

Requirements

A Master's degree or foreign equivalent in Data Science, Computer Science, or a related field, plus six years of experience in the position or a related occupation.
Alternatively, a Bachelor's degree or foreign equivalent in Data Science, Computer Science, or a related field, plus eight years of progressive experience in the position or a related occupation.
At least one year of prior experience serving as a 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.
At least one year of prior experience designing and implementing enterprise-grade data quality, discovery, and governance frameworks and tools from scratch.
At least one year of prior experience developing Artificial Intelligence and Machine Learning solutions for data quality, anomaly detection, and data discovery problems.
At least one year of prior experience leading cross-functional projects with engineering, product, analytics, and data science teams to deliver enterprise-wide data quality and governance solutions and drive rollout and adoption.
At least one year of prior experience collaborating with software engineering teams to improve event logging, enforce quality at the source, and manage complex logging frameworks.
At least one year of prior experience 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.
At least one year of prior experience with a data discovery platform such as DataHub, including developing custom integrations and data quality frameworks such as Deequ or Great Expectations.
At least five years of prior experience with data modeling, SQL, Airflow, Python, Java or Scala including Spark user-defined functions, and big data technologies including Spark, HDFS, YARN, Hive, Kafka, Flink, Elasticsearch, Grafana, and Presto.
At least five years of prior experience developing and optimizing distributed data pipelines using Apache Spark, including Spark on Kubernetes, supporting more than 10 TB of daily data volume and real-time pipelines processing millions of events per minute.
At least five years of prior experience designing and implementing multi-tier, highly scalable, distributed data pipelines and data warehouses in AWS or Google Cloud Platform, along with cloud-agnostic tooling, continuous integration and continuous delivery pipelines, serverless compute, and containerized deployments using Kubernetes.

Responsibilities

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.
Lead the design and implementation of custom integrations within data discovery frameworks such as DataHub for metadata-driven lineage and search.
Develop Artificial Intelligence and Machine Learning-based solutions for data quality, anomaly detection, and automated data discovery.
Extend and customize open-source data quality frameworks and tools such as Deequ and Great Expectations across critical datasets.
Design and implement robust batch and real-time data pipelines using Apache Spark for large-scale daily data volumes exceeding 10 TB and real-time pipelines processing millions of events per minute.
Build and maintain enterprise data warehouses and data solutions in AWS and Google Cloud Platform environments using big data technologies, ensuring operational stability and performance at petabyte scale.
Design and develop cloud-agnostic tooling, continuous integration and continuous delivery 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, Machine Learning 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.

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. 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.

From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines.

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:

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.
Design and implementation of enterprise-grade data quality, discovery, and governance frameworks and tools from scratch.
Developing Artificial Intelligence (AI) and Machine Learning (ML) solutions to solve data quality, anomaly detection, and data discovery problems.
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.
Collaborating with software engineering teams to improve event logging, enforce quality at the source, and manage complex logging frameworks.
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.
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:

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.
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.
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.

#LI-DNI

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 [email protected].

What should I know about Roku's culture?

Roku is a great place for people who want to work in a fast-paced environment where everyone is focused on the company's success rather than their own. We try to surround ourselves with people who are great at their jobs, who are easy to work with, and who keep their egos in check. We appreciate a sense of humor. We believe a fewer number of very talented folks can do more for less cost than a larger number of less talented teams. We're independent thinkers with big ideas who act boldly, move fast and accomplish extraordinary things through collaboration and trust. In short, at Roku you'll be part of a company that's changing how the world watches TV. 

We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002. 

To learn more about Roku, our global footprint, and how we've grown, visit https://www.weareroku.com/factsheet.

By providing your information, you acknowledge that you want Roku to contact you about job roles, that you have read Roku's Applicant Privacy Notice, and understand that Roku will use your information as described in that notice. If you do not wish to receive any communications from Roku regarding this role or similar roles in the future, you may unsubscribe at any time by emailing [email protected].

About the Company

Roku

Streaming hardware and ad-supported content

Roku provides a streaming entertainment ecosystem built around hardware devices (Roku TVs, streaming players, smart home gear, and audio gear) and a purpose-built operating system. Its devices run the Roku OS to deliver apps and streaming content to televisions. The Roku Channel offers free, ad-supported content and Roku Originals are exclusive programs produced in-house, bundled with advertising revenue and content distribution. The business model blends hardware sales, advertising, and distribution of content through its platform. Roku differentiates itself by offering a wide range of affordable devices, a centralized ad-supported free channel, and in-house originals, creating an integrated yet open platform for apps and content. The company’s goal is to grow a large, easy-to-use streaming ecosystem that combines hardware, software, and content to reach many households and monetize through device sales, ads, and distribution deals.

Company size: 1,001-5,000
Company stage: IPO
Headquarters: San Jose, CA
Founded: 2002

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