Data Engineer

Job Description

Responsibilities

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 Lead Data Engineer will be responsible for creating a connected data ecosystem that unleashes the power of our streaming data. 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)

Qualifications
• 1+ years 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, Python)
• 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.
• Bachelors' degree with a specialization in Computer Science, Engineering, Physics, 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

Jobcode: Reference SBJ-d9014m-3-145-106-87-42 in your application.