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Sr. Data Engineer - job 1 of 2

Company Description

NBCUniversal owns and operates over 20 different businesses across 30 countries including a valuable portfolio of news and entertainment television networks, a premier motion picture company, significant television production operations, a leading television stations group, world-renowned theme parks and a premium ad-supported streaming service.

Here you can be your authentic self. As a company uniquely positioned to educate, entertain and empower through our platforms, Comcast NBCUniversal stands for including everyone. We strive to foster a diverse and inclusive culture where our employees feel supported, embraced and heard. We believe that our workforce should represent the communities we live in, so that together, we can continue to create and deliver content that reflects the current and ever-changing face of the world. Click here to learn more about Comcast NBCUniversal’s commitment and how we are making an impact.

Job Description

As part of the global Operations & Technology organization, the D&A team is focused on data and analytics strategies for the future. We support NBCU’s vast portfolio of brands - from broadcast, cable, news, and sports networks to film studios, world-renowned theme parks, and a diverse suite of digital properties. We take pride in supplying our business groups with data to advise and shape strategic business decisions related to our content.

We're looking for a passionate problem solver who’s looking to build the next generation of data pipelines and applications to support our generative AI initiatives. Working across one or more of our main subject areas – research, marketing, engineering frameworks – the Sr Data Engineer role is right for you if you’re a “hands-on” coder who can build and cleanse large datasets in order to report out actionable insights.

In addition, you’ll be working with internal stakeholders, data engineers, visualization experts, data scientists, and other technologists across the business. If you’re someone who loves to take large, disparate data sets and build them into flexible and scalable analytics applications and databases, you’ve come to the right place. Here you can create the extraordinary. Join us!

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.
  • 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.
  • Strong 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)
  • 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.
  • Collaborate with business leaders, engineers, and product managers to understand data needs.
  • Create documentation for developers and business users to help them understand our products.
  • Implement the appropriate design patterns while optimizing performance, cost, security, and scale and end user experience
  • Collaborate with business leaders, engineers, and product managers to understand data needs.
  • Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using cloud-native data engineering principles

Qualifications

Basic Requirements:

  • 5+ years of experience in a data engineering or related role
  • Direct experience designing and building data modeling, ETL/ELT development principles, or data warehousing concepts
  • Strong knowledge of data management fundamentals and data storage principles
  • Deep experience in building data pipelines using Python/SQL 
  • Deep experience in Airflow or similar orchestration engines
  • Deep experience in applying CI/CD principles and processes to data engineering solutions.
  • Strong understanding of cloud data engineering design patterns and use cases
  • Bachelor's degree in Computer Science, Data Science, Statistics, Informatics, Information Systems, Mathematics, Computer Engineering, or quantitative field.

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: $115,000 -  $145,000

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 [email protected].

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.

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Average salary estimate

$130000 / YEARLY (est.)
min
max
$115000K
$145000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Sr. Data Engineer, NBCUniversal

If you're a seasoned Sr. Data Engineer looking to make waves, NBCUniversal invites you to step into an exciting role at our iconic headquarters in New York City! You're not just a coder; you're a data architect with the creative flair to build the next generation of data pipelines and applications while supporting our innovative generative AI initiatives. As part of our dynamic Data & Analytics team, you'll collaborate with talented data engineers, visualization experts, and data scientists, working across diverse areas like research, marketing, and engineering frameworks. Your mission? To transform vast, disparate datasets into insightful, actionable intelligence that drives strategic decisions across our extensive portfolio of entertainment, news, and digital properties. You’ll design, build, and scale data pipelines that stream seamlessly from various sources, while implementing best practices in data modeling, warehousing, and cloud-native engineering principles. Our culture is all about inclusivity and empowerment, so if you’re ready to embrace your authentic self and help foster a diverse environment while building robust analytics solutions, this is the perfect opportunity for you. Join us at NBCUniversal, where your creativity and technical skills will help shape the future of data-driven storytelling and entertainment!

Frequently Asked Questions (FAQs) for Sr. Data Engineer Role at NBCUniversal
What responsibilities does the Sr. Data Engineer at NBCUniversal have?

The Sr. Data Engineer at NBCUniversal is responsible for designing, building, and scaling data pipelines across various source systems, including cloud-based environments. You will collaborate with cross-functional teams to determine data requirements, interface with technology teams to manage data transformations, and ensure efficient integration strategies are implemented. This role also demands a solid understanding of data modeling and the ability to coach others in foundational data engineering principles.

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What qualifications are needed for the Sr. Data Engineer role at NBCUniversal?

To qualify for the Sr. Data Engineer position at NBCUniversal, candidates should have at least 5 years of relevant experience in data engineering or a similar field. A bachelor’s degree in Computer Science, Data Science, or a quantitative field is essential, alongside in-depth knowledge of data modeling, ETL/ELT principles, and strong programming skills in Python and SQL. Familiarity with tools like Airflow for orchestration and understanding cloud data engineering patterns is also crucial.

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What technologies will a Sr. Data Engineer at NBCUniversal work with?

In the role of Sr. Data Engineer at NBCUniversal, you will engage extensively with technologies related to data pipelines, including cloud-native platforms and orchestration tools like Airflow. You’ll utilize programming languages such as Python and SQL to manage data transformations and integrate multiple data sources. Additionally, a grasp of machine learning best practices will enhance your ability to contribute effectively to the team’s generative AI initiatives.

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What is the working environment for the Sr. Data Engineer position at NBCUniversal?

The Sr. Data Engineer position at NBCUniversal is fully remote, allowing you to contribute from your own home while staying connected with the team. This flexible working model supports a healthy work-life balance and ensures that you have the freedom to work in a manner that suits your personal and professional needs without the requirement of commuting to our New York headquarters.

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How does NBCUniversal support the professional development of its Sr. Data Engineers?

NBCUniversal is committed to investing in the professional development of its employees, including Sr. Data Engineers. You’ll have access to resources such as tuition reimbursement, training opportunities, and workshops to refine your skills. Moreover, you'll be able to work alongside experienced peers and thought leaders in the field, fostering an environment of continuous learning and growth.

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Common Interview Questions for Sr. Data Engineer
Can you describe your experience with data pipeline architecture as a Sr. Data Engineer?

In answering this question, focus on specific data pipeline projects you've worked on, detailing your role in designing and implementing the architecture. Mention the tools and technologies you used, how you optimized performance and scalability, and any challenges you overcame during the project. Be prepared to discuss metrics of success.

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How do you ensure data quality and integrity in your engineering processes?

It's important to outline your approach to maintaining data quality, including the methods you use for validation, cleansing, and monitoring data flows. Discuss specific techniques like automated quality checks or integration testing you’ve implemented and the impact these have on projects.

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What strategies do you use to optimize data retrieval and storage?

Share your insights on data modeling and storage principles. Discuss techniques you employ to optimize data retrieval, such as proper indexing, partitioning strategies, or caching mechanisms. Highlight any real-world applications of these strategies in your past roles.

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Can you explain the ETL process you've developed in a previous project?

Provide a clear summary of a specific ETL process you've worked on, detailing the extraction sources, transformation steps, and loading destinations. Highlight your role, the challenges faced, and the outcomes achieved, ensuring to mention any tools used during the process.

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How do you approach collaboration with cross-functional teams?

Discuss your communication style and methods for engaging with various stakeholders, such as data scientists, product managers, and engineers. Provide examples of how you've facilitated discussions to understand their data needs and driven collaborative solutions.

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What tools do you prefer for orchestration and why?

Highlight your preferred orchestration tools, such as Airflow, and explain why you choose them over others. Discuss specific features that make these tools effective for managing workflows and ensuring proper scheduling and monitoring of data pipelines.

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Could you explain your experience with machine learning in data engineering?

In your response, describe how you’ve applied machine learning concepts in data engineering projects. Discuss any specific algorithms you used, the data preparation process, and how the integration of ML enhanced the analytical capabilities of the applications you developed.

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How do you stay current with trends in data engineering?

Talk about the resources you leverage to keep up with new technologies and trends in data engineering, such as blogs, webinars, or online courses. Mention any professional networks you’re involved with and how these resources inform your work and decision-making.

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What documentation practices do you follow in your work?

Stress the importance of documentation in data engineering. Detail the types of documentation you regularly produce, such as technical specifications, data dictionaries, or user guides for business stakeholders, and demonstrate how these practices enhance collaboration and maintenance.

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How do you manage performance issues in your data pipelines?

Be prepared to discuss your approach to identifying and resolving performance bottlenecks in data pipelines. Include methodologies you use, like profiling and monitoring tools, and share examples of how you've effectively improved performance based on these metrics.

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We are in business to create and deliver content so compelling it entertains, informs and shapes our world. We believe that the talent, creativity and diversity of our people are our greatest resources. We take our business seriously, but do no...

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Full-time, remote
DATE POSTED
December 17, 2024

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