Data Engineer – Engineering & Operations

🔥 1 minute ago

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Logo of NBCUniversal

NBCUniversal

10,000+ employees

Founded 2004

📱 Media

Media • Entertainment

NBCUniversal is a leading global media and entertainment company known for creating and distributing content across a variety of platforms. With over 100 years of experience, it is a part of Comcast and encompasses brands like Peacock, NBC Sports, and many others to educate, entertain, and empower audiences around the world. The company is involved in television broadcasting, film production, and theme parks, and is also recognized for its initiatives in technology and corporate social responsibility. NBCUniversal is committed to innovation and social impact, making it a vibrant workplace for media and tech professionals.

📋 Description

• Design, build, and operate scalable data pipelines, clean room environments, identity workflows, and privacy-safe data integrations that support NBCUniversal’s data collaboration ecosystem • Support partner onboarding into clean room environments across platforms • Configure and manage clean room environments, including data access, environment setup, platform configuration, and release validation • Implement privacy-preserving controls such as aggregation thresholds, anonymization techniques, approved query patterns, and output validation checks • Deploy and manage Python-based libraries, templates, and reusable components within the clean room and data platform ecosystem • Design, implement, and enforce granular role-based access control policies across data platform environments • Design, build, and operate scalable ELT pipelines using advanced SQL, Snowpark, PySpark, dbt, or similar technologies • Implement and evolve identity resolution logic that maps internal NBCU data to third-party identifiers

🎯 Requirements

• Bachelor’s degree or equivalent practical experience in Computer Science, Information Systems, Software Engineering, Electrical Engineering, Electronics Engineering, Data Engineering, or a related technical field • 3+ years of experience in data engineering, including building and operating production data pipelines, data models, and data products • Deep proficiency in advanced SQL and Python for data processing, automation, pipeline development, validation, and operational support • 2+ years of hands-on experience with cloud data platforms such as Snowflake, Databricks, or similar technologies • Experience building scalable ELT pipelines using tools such as Airflow, dbt, Snowpark, PySpark, or similar technologies

🏖️ Benefits

• medical, dental and vision insurance • 401(k) • paid leave • tuition reimbursement • a variety of other discounts and perks

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