Senior Data Engineer (Data Governance Lead)

Join Roku as a Senior Data Engineer (Data Governance Lead) and lead the technical architecture, design, and development of enterprise data quality, discovery, and governance frameworks. You will establish and enforce data governance standards, develop AI/ML-based solutions, design and implement data pipelines, and provide technical leadership to engineers and consultants. This role offers a competitive salary, unlimited paid time off, and the opportunity to work from home.

About Roku

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

Responsibilities

• Lead the 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.
• 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.
• Collaborating with software engineering teams to improve event logging, enforce quality at the source, and manage complex logging frameworks
• 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
• Data discovery platform like Datahub, including developing custom integrations and data quality frameworks like Deequ or Great Expectations
• 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
• Developing Artificial Intelligence (AI) and Machine Learning (ML) solutions to solve data quality, anomaly detection, and data discovery problems

Requirements

• 6 years of experience in the position or a related occupation
• Master’s degree or foreign equivalent in Data Science, Computer Science, or related field
• 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:
• 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
• Design and implementation of enterprise-grade data quality, discovery, and governance frameworks and tools from scratch
• Must have at least 5 years of prior work experience in the following:
• 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
• 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