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Manager of Data Quality - Data Engineering, Peacock

Company Description

We create world-class content, which we distribute across our portfolio of film, television, and streaming, and bring to life through our theme parks and consumer experiences. We own and operate leading entertainment and news brands, including NBC, NBC News, MSNBC, CNBC, NBC Sports, Telemundo, NBC Local Stations, Bravo, USA Network, and Peacock, our premium ad-supported streaming service. We produce and distribute premier filmed entertainment and programming through Universal Filmed Entertainment Group and Universal Studio Group, and have world-renowned theme parks and attractions through Universal Destinations & Experiences. NBCUniversal is a subsidiary of Comcast Corporation.

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. Our Diversity, Equity and Inclusion initiatives, coupled with our Corporate Social Responsibility work, is informed by our employees, audiences, park guests and the communities in which we live. We strive to foster a diverse, equitable and inclusive culture where our employees feel supported, embraced and heard. Together, we’ll continue to create and deliver content that reflects the current and ever-changing face of the world.

Job Description

Our Direct-to-Consumer (DTC) portfolio is a powerhouse collection of consumer-first brands, supported by media industry leaders, Comcast, NBCUniversal and Sky. When you join our team, you’ll work across our dynamic portfolio including Peacock, NOW, Fandango, SkyShowtime, Showmax, and TV Everywhere, powering streaming across more than 70 countries globally. And the evolution doesn’t stop there. With unequalled scale, our teams make the most out of every opportunity to collaborate and learn from one another. We’re always looking for ways to innovate faster, accelerate our growth and consistently offer the very best in consumer experience. But most of all, we’re backed by a culture of respect. We embrace authenticity and inspire people to thrive. 

As part of the Direct-to-Consumer Decision Sciences team, the Manager of Data Quality will be responsible for overseeing a critical function that bridges data management with operational excellence. The role requires strong cross-functional collaboration skills to effectively engage with software engineering, data analytics, and elements of machine learning to understand data quality requirements and deliver effective solutions.

In this role, the Manager of Data Quality will share responsibilities in the development and operation of Data Quality monitors, automation to optimization of data quality pipelines that facilitate deeper analysis and reporting by the business, as well as support ongoing operations related to the Direct to Consumer data ecosystem. The candidate will act as a liaison between data engineering and other teams, advocating for data-driven decision making and best operational practices.

Responsibilities include, but are not limited to:

  • Help manage a high-performance team of Data Quality Engineers and Data Quality Analysts
  • Contribute to and lead the team in design, build, testing, scaling and maintaining Data Quality monitors built in-house as well as 3rd party products, according to business and technical requirements.
  • Evaluate and select appropriate technologies and tools for data quality monitoring, ensuring alignment with organizational goals and industry best practices
  • Help Data Engineering organization deliver observable, reliable and secure data quality monitors, embracing “you build it you run it” mentality, and focus on automation and GitOps.
  • Continually work on improving the codebase and have active participation and oversight in all aspects of the team, including agile ceremonies.
  • Take an active role in story definition, assisting business stakeholders with acceptance criteria.
  • Work with Data Engineering Directors to share and contribute to the broader technical vision.
  • Develop and champion best practices, striving towards excellence and raising the bar within the department.
  • Research methods of data anomaly detection using broad range of techniques, including statistical and Machine Learning

Qualifications

  • 5+ years relevant experience in Data Engineering or Data Analytics or Machine Learning
  • Strong leadership skills with the ability to lead and mentor a team of data engineers Experience in using techniques such as infrastructure as code and CI/CD
  • Experience with graph-based data workflows using Apache Airflow
  • Programming skills in one or more of the following: Python, Java, Scala, R and experience in writing reusable/efficient code to automate analysis and data processes Experience in processing large volumes of data using parallelism techniques/tooling, such as Apache Spark
  • Experience in processing structured and unstructured data into a form suitable for analysis and reporting with integration with a variety of data metric providers ranging from advertising, web analytics, and consumer devices
  • Experience in basic Machine Learning techniques is a big plus
  • Experience with working in large scale SQL
  • Understanding of pillars of Data Quality: Completeness, Timeliness, Validity, Uniqueness, Consistency, Accuracy (or similar)
  • Bachelors’ degree with a specialization in Computer Science, Engineering, Physics, other quantitative field or equivalent industry experience.

Desired Characteristics

  • Experience with large-scale video assets
  • Ability to work effectively across functions, disciplines, and levels
  • Team-oriented and collaborative approach with a demonstrated aptitude, enthusiasm and willingness to learn new methods, tools, practices and skills
  • Ability to recognize discordant views and take part in constructive dialogue to resolve them
  • Pride and ownership in your work and confident representation of your team to other parts of NBCUniversal

Additional Requirements:

Hybrid: This position has been designated as hybrid, generally contributing from the office a minimum of three days per week.

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 and long-term incentive eligible). 

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].

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What You Should Know About Manager of Data Quality - Data Engineering, Peacock, NBCUniversal

Join Peacock as the Manager of Data Quality within our Data Engineering team, where you'll play a pivotal role in ensuring we maintain the highest standards of data integrity across our extensive suite of brands. Peacock, a leader in streaming entertainment, is looking for someone who thrives on collaboration and is passionate about making data-driven decisions. In this exciting role, you’ll work closely with software engineering, data analytics, and machine learning teams to oversee the development of robust Data Quality monitors while championing best practices within the organization. You will contribute to the design, testing, and maintenance of innovative data quality solutions that empower deeper analysis and reporting capabilities. As part of a high-performance team, you’ll mentor Data Quality Engineers and Analysts, fostering a culture of excellence and continuous improvement. Your technical acumen will shine as you evaluate and select tools for monitoring data quality, ensuring they align with our goals and industry benchmarks. With a focus on automation, you will implement cutting-edge solutions that will enhance efficiency and reliability in our data processes. Plus, you’ll have the opportunity to take part in defining stories alongside business stakeholders and sharing your insights into the broader technical vision within our data ecosystem. Here at Peacock, we celebrate creativity and diversity, so if you’re ready to make an impact and drive innovation, this is the role for you!

Frequently Asked Questions (FAQs) for Manager of Data Quality - Data Engineering, Peacock Role at NBCUniversal
What are the responsibilities of the Manager of Data Quality at Peacock?

The Manager of Data Quality at Peacock is responsible for overseeing the development and operation of Data Quality monitors, managing a team of Data Quality Engineers and Analysts, and leading initiatives aimed at optimizing data quality pipelines. This role requires strong collaboration skills to engage effectively with data engineering, analytics, and machine learning teams, ensuring that data-driven decision-making is prioritized throughout the organization.

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What qualifications are needed for the Manager of Data Quality position at Peacock?

To be considered for the Manager of Data Quality position at Peacock, candidates should have at least 5 years of experience in Data Engineering, Data Analytics, or Machine Learning. A Bachelor’s degree in a related field is essential, along with strong leadership skills and a proven ability to manage and mentor teams. Familiarity with programming languages such as Python or Java and experience with data quality frameworks and tools are also crucial.

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How does the Manager of Data Quality ensure high data quality standards at Peacock?

The Manager of Data Quality at Peacock ensures high data quality standards by developing and implementing effective monitoring systems that assess the completeness, accuracy, and timeliness of data. They will be heavily involved in establishing best practices for data quality and collaborating with cross-functional teams to address any data quality issues proactively. Continuous improvement and automation play a key role in their strategy to maintain data integrity.

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What technologies and tools does the Manager of Data Quality at Peacock utilize?

The Manager of Data Quality at Peacock utilizes various technologies and tools to monitor and manage data quality. This includes using Apache Airflow for managing workflows, as well as programming in Python or Scala to automate data processes. The role also involves selecting the right tools and technologies for data quality monitoring that align with organizational objectives and adhere to industry best practices.

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What is the work culture like for the Manager of Data Quality at Peacock?

The work culture for the Manager of Data Quality at Peacock emphasizes collaboration, respect, and innovation. Employees are encouraged to express authenticity and bring their unique perspectives to the team. Being part of a diverse and inclusive environment means that everyone's ideas are valued, and there are ample opportunities to learn and grow in a supportive setting.

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Common Interview Questions for Manager of Data Quality - Data Engineering, Peacock
Can you explain your experience with data quality frameworks?

When answering this question, provide specific examples of frameworks you've implemented in previous roles. Highlight your understanding of key data quality principles such as accuracy, completeness, and timeliness, and describe how your frameworks have positively impacted data integrity and business decisions.

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How do you approach mentoring junior data quality engineers?

Discuss your mentoring philosophy and any successful strategies you've used in the past. Highlight the importance of setting clear goals, providing constructive feedback, and fostering an environment where junior engineers feel comfortable asking questions and sharing ideas.

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What techniques do you use for data anomaly detection?

Mention a few key techniques such as statistical methods or machine learning approaches you have used to detect anomalies in data. Illustrate your knowledge by explaining a specific instance where these techniques were successful in identifying issues.

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How do you ensure alignment between data quality practices and business objectives?

Explain your strategy for collaborating with business stakeholders and understanding their needs. You could mention how you align data quality indicators with KPIs and ensure that your team is focused on delivering value that meets organizational goals.

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Can you give an example of a successful data quality project you've led?

Share a brief case study of a data quality project where you played a key role, detailing your contribution, the challenges faced, and the outcomes. Highlight skills such as project management, technical expertise, and team collaboration.

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What programming languages are you proficient in, and how have you used them in your past roles?

List the programming languages you are familiar with, providing examples of how you have applied them in data analysis or engineering tasks. Emphasize your experience with automation or developing data pipelines.

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How do you prioritize tasks in a fast-paced environment?

Describe your approach to prioritization, such as using agile methodologies or managerial frameworks like Eisenhower's Matrix. Provide an example of a time you successfully managed competing priorities.

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What experience do you have with data processing tools like Apache Spark?

Discuss your hands-on experience with Apache Spark, including examples of large data sets you've processed. Highlight your understanding of parallel processing techniques and how they can enhance data quality efforts.

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How do you stay updated with the latest trends in data quality and engineering?

Mention resources or networks you engage with to stay informed about the latest trends in data quality. This could include attending conferences, following industry leaders, or participating in online forums.

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Can you describe a challenging data quality issue you've encountered and how you resolved it?

Provide a detailed example of a complex data quality issue, focusing on your analytical process, the resolution steps you took, and the final outcome. This showcases your problem-solving skills and ability to think critically under pressure.

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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, hybrid
DATE POSTED
December 10, 2024

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