Data Engineer II

Job Summary

As a Data Engineer II, you’ll apply your passion for data, along with experience working with large‑scale datasets, data pipelines, and distributed data systems, to help our team meet the goal of delivering the best personalized experience for our hundreds of millions of subscribers worldwide.

• Design, craft, and own high‑quality foundational datasets to produce reliable, meaningful inputs for machine learning models and subscriber experiences.
• Source, analyze, and validate diverse upstream data sources from partner teams and raw signals using exploratory data analysis.
• Identify and build new user and content data features for recommendation systems through collaboration with machine learning engineers.
• Enhance existing feature quality through experimentation, analysis, and iterative development.
• Build, optimize, and maintain large‑scale data processing jobs, pipelines, and workloads.
• Improve data quality and reliability by implementing checks, anomaly detection, testing, monitoring, and alerting.
• Contribute to operational excellence by following observability best practices and participating in an on‑call rotation to support critical production data pipelines.

• Bachelor’s degree in Computer Science (or related field), or equivalent work experience.
• At least 3 years of experience working with large‑scale data workloads, building and curating datasets, and developing data pipelines and processing jobs.
• Strong programming skills in Python, Java, or a comparable object‑oriented language.
• Experience working with Databricks or equivalent large‑scale data processing platforms.
• Demonstrated knowledge of operating within a Public Cloud Provider (e.g., AWS, Microsoft Azure, Google Cloud).
• Experience with source control systems and CI/CD pipelines.
• Strong grasp of computer science fundamentals (data structures, algorithms, design patterns, etc.).
• Strong communication skills, both written and verbal.

• Proficiency working in Databricks to build data pipelines.
• Experience with distributed data processing frameworks, such as Apache Spark.
• Knowledge of messaging technologies (e.g., Kafka, Kinesis, SQS).
• Familiarity with recommendation system industry architectures and best practices.
• Hands‑on experience with No
  
  SQL data stores (e.g., DynamoDB, Cassandra, ScyllaDB).
• Experience using AI and coding assistants to accelerate design and development.

Salary range:
Seattle, WA and New York, NY – $112,000 to $150,100 per year;
Santa Monica, CA – $106,900 to $143,300 per year. Base pay will vary based on internal equity and candidate qualifications. A bonus and/or long‑term incentive units may be provided, as well as a full range of medical, financial, and other benefits.

Seattle, WA or New York, NY (with options for Santa Monica, CA).