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SalaryOur 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 an unequaled 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 the 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 Data Engineer will be responsible for creating a connected data ecosystem that unleashes the power of our streaming data with a focus on international propositions. We gather data from across all customer/prospect journeys in near real-time, to allow fast feedback loops across territories; combined with our strategic data platform, this data ecosystem is at the core of being able to make intelligent customer and business decisions.
In this role, the Data Engineer will share responsibilities in the development and maintenance of optimized and highly available data pipelines that facilitate deeper analysis and reporting by the business, as well as support ongoing operations related to the Direct-to-Consumer data ecosystem.
Responsibilities include, but are not limited to:
- Develop and maintain batch and streaming data pipelines according to business and technical requirements.
- Deliver observable, reliable and secure software, embracing “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)
Responsibilities include, but are not limited to:
- Help manage a high-performance team of Data Engineers
- Contribute to and help lead 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 “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 hypothesis, and deliver key insights
- Operationalize data processing systems (dev ops)
