Data Engineer, Operations

Role Overview

Data Engineer (Operations) reporting to the Director of Engineering & Operations. You will design, build, and maintain scalable data pipelines and privacy-safe data integration workflows to support NBCUniversal’s data collaboration ecosystem.

Responsibilities

• Design and operate scalable data pipelines supporting partner onboarding, audience activation, measurement, and reporting.
• Support partner onboarding into clean room environments across platforms (e.g., Snowflake, LiveRamp, Databricks), ensuring secure and privacy-preserving configurations.
• Configure and manage clean room environments, including data access controls, environment setup, and platform validation.
• Implement privacy-preserving controls (e.g., aggregation thresholds, anonymization, output validation) to meet privacy standards.
• Develop reusable Python libraries, templates, and components for repeatable data workflows.
• Build and operate ELT pipelines for ingestion, transformation, and delivery using tools such as SQL, Snowpark, and PySpark.
• Create curated datasets for audience activation, measurement, and reporting with strong data quality and reliability.
• Work on identity resolution workflows (responsibilities continue beyond the provided text).

Requirements

• Bachelor’s degree (or equivalent practical experience) in a related technical field.
• 3+ years of production data engineering experience (building and operating production pipelines/data products).
• Deep proficiency in SQL and Python for processing, automation, and operational support.
• 2+ years hands-on experience with cloud data platforms such as Snowflake and/or Databricks.
• Experience building scalable ELT pipelines with tools like Airflow, dbt, Snowpark, or PySpark.
• Strong fundamentals in data modeling, data warehousing, and data integration best practices.
• Knowledge of data security and privacy controls, including role-based access management.
• Strong troubleshooting and problem-solving skills.
• Effective communication and cross-functional collaboration.

Nice to Have

• Experience with clean room implementations and privacy-preserving data collaboration patterns (explicitly referenced in responsibilities).