Job Description

We are seeking a Staff Data Engineer looking to build the next generation of data pipelines and applications across the development of innovative new systems and solutions using a rapidly changing landscape of emerging technologies, including generative AI and large language models. Working across the practices, techniques and tools used for the operational management of large language models in production environments – the Staff Data Engineer role is proper for you if you're a subject matter expert in designing data integration frameworks and pipelines and still love to jump in and be "hands-on" when needed. This team is focused on proving the value of new tech and bringing it to production quickly.

You'll have the opportunity to partner with internal stakeholders, data engineers, visualization experts, data scientists, and other technologists across the businesses. You've come to the right place if you love to take large, disparate data sets and build them into flexible and scalable analytics applications and warehouses. In addition, you are well-versed in designing, building, and supporting APIs, machine learning services and frameworks, LLMs, lang-chain, and foundational data warehousing technologies.

Your primary focus will be building reliable, scalable, and efficient pipelines for use in LLMs and crafting our vision for LLM analytics. You will be essential in defining the team's strategy, evaluating, and integrating data patterns and technologies, and building pipelines alongside domain experts and data scientists.

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.

Qualifications

• 8+ 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 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.

Desired Characteristics:

• 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.
• Proven adaptability in a fast-paced, evolving technology landscape, with a strong problem-solving ability and quick learning curve.
• Effective communication skills, capable of working collaboratively across diverse teams and navigating a large, matrixed organization efficiently.
• Ability to translate business needs into clear technical requirements.
• Analytical – You have experience in delivering self-service analytics solutions that promote data discovery.
• Experience with Snowflake, Amazon Web Services, or related cloud platforms a plus
• Understanding of big data technology stacks (Hive / Spark etc) is a plus
• Experience moving on prem technologies to the cloud is a plus
• Action-oriented – You're constantly figuring out new problems and are regularly showing results with a positive attitude, always displaying ethical behavior, integrity, and building trust
• Strong understanding of Agile principles and best practices
• You’ve dealt with ambiguity and can make quality decisions in a dynamic, fast-paced environment

Additional Requirements:

• Fully Remote: This position has been designated as fully remote, meaning that the position is expected to contribute from a non-NBCUniversal worksite, most commonly an employee’s residence.

This position is eligible for company sponsored benefits, including medical, dental and vision insurance, 401(k), paid leave, tuition reimbursement, and a variety of other discounts and perks. Learn more about the benefits offered by NBCUniversal by visiting the Benefits page of the Careers website. Salary range: $130,000 - $170,000 (bonus eligible)

We are accepting applications for this position on an ongoing basis.

Additional Information

As part of our selection process, external candidates may be required to attend an in-person interview with an NBCUniversal employee at one of our locations prior to a hiring decision. NBCUniversal's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law.

If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation. You can submit your request to AccessibilitySupport@nbcuni.com.

For LA County and City Residents Only: NBCUniversal will consider for employment
qualified applicants with criminal histories, or arrest or conviction records, in a manner
consistent with relevant legal requirements, including the City of Los Angeles' Fair Chance
Initiative For Hiring Ordinance, the Los Angeles' County Fair Chance Ordinance for Employers, and the California Fair Chance Act, where applicable.