Data Engineer, Engineering & Operations
Listed on 2026-07-13
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IT/Tech
Data Engineering
Data Engineer, Engineering & Operations — Remote
NBCUniversal is one of the world's leading media and entertainment companies. We create world‑class content, which we distribute across our portfolio of film, television, and streaming, and bring to life through our global theme park destinations, consumer products, and experiences. We own and operate leading entertainment and news brands, including NBC, NBC News, NBC Sports, Telemundo, NBC Local Stations, Bravo, and Peacock, our premium ad‑supported streaming service.
We produce and distribute premier filmed entertainment and programming through our powerhouse film and television studios, including Universal Pictures, Dream Works Animation, and Focus Features, and the four global television studios under the Universal Studio Group banner, and operate industry‑leading theme parks and experiences around the world through Universal Destinations & Experiences, including Universal Orlando Resort, home to Universal Epic Universe, and Universal Studios Hollywood.
NBCUniversal is a subsidiary of Comcast Corporation. Visit for more information.
Our impact is rooted in improving the communities where our employees, customers, and audiences live and work. We have a rich tradition of giving back and ensuring our employees have the opportunity to serve their communities. We champion an inclusive culture and strive to attract and develop a talented workforce to create and deliver a wide range of content reflecting our world.
Job DescriptionWe are seeking a Data Engineer to join the Engineering & Operations team. Reporting to the Director of Engineering & Operations
, this role will design, build, and operate scalable data pipelines, clean room environments, identity workflows, and privacy‑safe data integrations that support NBCUniversal’s data collaboration ecosystem.
The ideal candidate is a hands‑on data engineer with strong SQL and Python skills, experience working with cloud data platforms such as Snowflake or Databricks, and the ability to build secure, reliable, and repeatable data workflows for partner onboarding, audience activation, measurement, and reporting.
Responsibilities
Clean Room & Partner Onboarding
- Support partner onboarding into clean room environments across platforms such as Snowflake, Live Ramp, Databricks, or similar technologies.
- Follow clean room architecture patterns that are secure, scalable, privacy‑preserving, and repeatable across partner engagements.
- Configure and manage clean room environments, including data access, environment setup, platform configuration, and release validation.
- Serve as the technical owner for assigned partner onboarding efforts, coordinating with product, engineering, operations, privacy, and partner‑facing teams.
- Implement privacy‑preserving controls such as aggregation thresholds, anonymization techniques, approved query patterns, and output validation checks.
Infrastructure Setup & Library Deployment
- Deploy and manage Python‑based libraries, templates, and reusable components within the clean room and data platform ecosystem.
- Support environment setup, configuration management, package deployment, and version‑controlled release processes.
- Partner with software engineering teams to operationalize reusable libraries for audience, measurement, reporting, and partner‑facing workflows.
- Ensure platform components are deployed consistently across partner environments and aligned with established engineering standards.
Security, RBAC & Privacy Controls
- Design, implement, and enforce granular role‑based access control policies across data platform environments.
- Configure least‑privilege service accounts, roles, grants, schemas, shares, and data access patterns.
- Partner with security, privacy, and platform teams to ensure access controls meet internal policies and partner‑specific requirements.
- Validate that partner‑facing outputs adhere to privacy, security, and business requirements before release.
- Design, build, and operate scalable ELT pipelines using advanced SQL, Snowpark, PySpark, dbt, or similar technologies.
- Develop and provision curated Gold datasets for audience, measurement, activation, and reporting use cases.
- Build…
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