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Senior Data Engineer, Global Streaming

2 months ago

Brentford, Greater London, United Kingdom NBCUniversal Full time
Job Description

About the Role

NBCUniversal is seeking a highly skilled Data Engineer to join our Direct-to-Consumer Decision Sciences team. As a Data Engineer, you will play a critical role in creating a connected data ecosystem that unleashes the power of our streaming data, with a focus on international propositions.

Key Responsibilities

  • Develop and maintain batch and streaming data pipelines according to business and technical requirements.
  • Deliver observable, reliable, and secure software, embracing a 'you build it, you run it' mentality, and focus on automation.
  • Continually work on improving the codebase and have active participation in all aspects of the team, including agile ceremonies.
  • Take an active role in story definition, assisting business stakeholders with acceptance criteria.
  • Work with Principal Engineers and Architects to share and contribute to the broader technical vision.
  • Practice and champion best practices, striving towards excellence and raising the bar within the department.
  • Operationalize data processing systems (DevOps) and system observability (SRE).

Additional Responsibilities

  • Help manage a high-performance team of Data Engineers.
  • Contribute to and help lead the team in design, build, testing, scaling, and maintaining data pipelines from a variety of source systems and streams (Internal, third-party, cloud-based, etc.), according to business and technical requirements.
  • Deliver observable, reliable, and secure software, embracing a '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 Principal Engineers and Architects to share and contribute to the broader technical vision.
  • Develop and champion best practices, striving towards excellence and raising the bar within the department.
  • Develop solutions combining data blending, profiling, mining, statistical analysis, and machine learning, to better define and curate models, test hypotheses, and deliver key insights.
  • Operationalize data processing systems (DevOps).

Requirements

  • 3-5 years of relevant experience in Data Engineering.
  • Experience of near Real-Time & Batch Data Pipeline development in a similar Big Data Engineering role.
  • Programming skills with an OOP language (e.g., Java, C++).
  • Proficient with SQL.
  • Experience working in a cloud environment such as Google Cloud Platform or AWS.
  • Hands-on programming experience of the following (or similar) technologies: Kubernetes, Docker, Apache Beam, Apache Flink, Apache Spark, Google BigQuery, Snowflake, Google BigTable, Google Pub/Sub, Kafka, Apache Airflow.
  • Experience implementing observability around data pipelines using SRE best practices.
  • 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.
  • Bachelor's degree with a specialization in Computer Science, Engineering, Physics, or other quantitative field, or equivalent industry experience.

Desired Characteristics

  • Strong Test-Driven Development background, with understanding of levels of testing required to continuously deliver value to production.
  • 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 the organization.