Principal Data Engineer

NBCUniversal is one of the world's leading media and entertainment companies. The Principal Data Engineer will drive the overall delivery and support of data and AI applications, design and build new systems while enhancing existing tech stacks, and collaborate with various stakeholders to fulfill analytics needs.

Responsibilities:

• Design, build, and scale data pipelines across a variety of source systems and streams (internal, third-party, and cloud-based), distributed/elastic environments, and downstream applications and self-service solutions
• Deep understanding of Machine Learning best practices (e.g., training/serving, feature engineering, feature/model selection, imbalance data, RAG patterns) and algorithms (e.g., deep learnings, optimization)
• Solid understanding of data modeling, warehousing, and architecture principles
• Implement appropriate design patterns while optimizing performance, cost, security, and scale and end-user experience
• Collaborate with cross-functional teams to understand data requirements and develop efficient data acquisition and integration strategies
• Interface with other technology teams to extract, load, and transform data from a wide variety of data sources using cloud-native data engineering principles
• Become a subject matter expert for data engineering-related technologies and designs
• Coach and guide others within the organization to build scalable pipelines based on foundational data engineering principles
• Participate in development sprints, demos, and retrospectives alongside releases and deployment
• Build and manage relationships with supporting engineering teams to deliver work products to production effectively
• Have worked well with data scientists, business analysts, and machine learning infrastructure to connect the dots between business and technology partners
• Develop automated tests for your code, ensuring every function, service, and object is compatible with your team's work and with the many systems within the NBCUniversal system portfolio and cross-device and browser compatibility
• Create documentation for developers and business users to help them understand our products
• Work collaboratively with a multidisciplinary team within a matrixed organization, leveraging strong interpersonal skills to navigate system complexities and deploy solutions efficiently
• Deploy to cloud-based platforms and troubleshoot application, cloud, and configuration issues when necessary
• Utilize tools for code & test generation to dramatically accelerate the delivery of features and components you create

Requirements:

• 13+ years of experience in a data engineering role, with a strong emphasis on leading data engineering teams
• Ability to think critically about problems, decipher user preferences versus challenging requirements, and effectively use online and onsite resources to find appropriate solutions
• Proven experience designing and deploying large-scale AI systems
• Deep understanding of data structures, algorithms, and system architecture
• Proven ability to thrive in an agile development environment, adept at incorporating feedback and adjusting to changing priorities
• Understanding REST-based APIs, vectorized embeddings, and other Retrieval Augmented Generation AI workload components
• Direct experience with data modeling, ETL/ELT development principles, cloud development, and data warehousing concepts
• Knowledge of cloud technologies such as AWS, Azure, GCP
• Knowledge of data management fundamentals and data storage principles
• Experience in building data pipelines using Python/SQL or similar programming languages
• General understanding of cloud data engineering design patterns and use cases
• Bachelor's degree in computer science, Data Science, Statistics, Informatics, Information Systems or related field
• Familiarity with integrating large language models and AI-generated content technologies into applications
• Familiarity with the development ecosystem evolving around LLM integration, such as Langchain, Claude Agent SDK
• Experience with Snowflake, Amazon Web Services, or related cloud platforms a plus
• Experience moving on prem technologies to the cloud is a plus