Discovery, Inc. is the global leader in real life entertainment. We serve passionate fans with content that inspires, informs, and entertains, providing leadership across deeply loved and trusted brands, such as Discovery Channel, TLC, Animal Planet, HGTV, Food Network, and Travel Channel. Available in 220 countries and territories and 50 languages, Discovery reaches viewers on all screens and services, from free-to-air and pay-TV channels, to digital products and streaming services, to social and mobile-first content and formats. Discovery delivers over 8,000 hours of original programming each year.
Discovery's Digital group is a well-funded start-up within Discovery, Inc. We are fast, nimble, and have fun developing new, innovative, and immersive digital products and content for iconic brands. We are working at the crossroads of technology, entertainment, and every day utility. As content creators across the digital ecosystem, we continuously leverage our technology to create immersive viewing and interactive experiences. We tell engaging stories to millions of viewers across the Internet every day, and bring new interactive experiences to life to not only entertain, but improve the lives of our customers.
We are hiring a Data Engineer in Bellevue, Washington to help build, scale, and maintain the data infrastructure needed to transform data into actionable insights and science-driven capabilities across our food, home, and lifestyle products. The Data Engineer will bring their skills and experience to the Data Science and Analytics team to advise and create a scalable data ecosystem that encompasses the many data elements produced across our direct-to-consumer products and apps.
This role will build new data pipelines, create new datasets, scale existing data sets, and create innovative data solutions to support consumer products across mobile, tablets, web, connected TV, voice, and emerging technologies. They will use big data platforms, data warehousing, and business intelligence technology to enable data science, machine learning, and self-service visualization analytics to drive these insights and product capabilities. This engineer will ensure the ongoing performance of reliable and efficient data systems using AWS and other data technologies.
An ideal candidate will be a driven, passionate advocate for building and maintaining highly scalable data systems, and using that data to support analytics and solutions that produce great experiences for our customers. This person will make data-driven decisions, have an insatiable curiosity, and obsess about their customers. They will have a strong point of view but remain open-minded should evidence lead in another direction. They are a team players whom others enjoy working with because they are reliable, innovative, and care for their team members. They build trust with people from all areas of the business and have a proven track record. This engineer takes end-to-end ownership and consistently delivers results in a fast-paced environment.
1. Partner with product, marketing, engineering, and analytics stakeholders to understand what data structures and systems are needed to support key business goals and processes.
2. Work with engineering and partner teams to identify scalable, accessible data sources for analysis and operational use.
3. Design, build, maintain, and improve a scalable data architecture and infrastructure to deliver customer, product, and marketing insights.
4. Design and build new/expanded data sets used to drive insights and models.
5. Partner closely with data analytics and scientists to deliver actionable insights, analytics, and science-driven models (e.g. using machine learning or other modeling techniques).
6. Prepare redundant and scalable systems that efficiently use resources and elegantly handle disruptions.
7. Ensure data integrity and accuracy across all owned data systems and sources.
8. Partner with central data warehousing team to ensure all relevant data is accessible enterprise-wide and meets common standards.
9. Make data engineering techniques approachable and understandable to non-data engineers or scientists.
10. Support the hiring and development of other data engineers, scientists, analysts, and other technical professionals, helping them enhance their skills, while supporting a fun and engaging culture.
* Minimum of 3+ years of proven technical experience in data engineering, data warehousing, and analytics.
* Expertise in structuring, cleansing, and preparing large, complex datasets for analysis and modeling.
* Expertise in building robust and scalable data pipelines using structured and unstructured data as well as batch data and real time streaming data services.
* Expertise with SQL and other data querying techniques (Scala, Shell Scripting, Python, etc…).
* Experience with Apache Spark and Presto.
* Expertise in data warehousing solutions and techniques.
* Experience with Amazon Web Services (Redshift, S3, EC2, EMR, etc.) is required.
* Experience with Adobe Analytics is a plus.
* Experience with statistical programming languages, such as Python or R is a plus.
* Demonstrated ability to work across product, engineering, and analytics teams to evaluate new ideas, discuss technical concepts, create scalable designs, and make tradeoffs to remove roadblocks.
* Strong written and verbal communication skills. Can communicate the results of your work clearly to your audience.
* Master’s degree in quantitative or technical field (engineering, statistics, computer sciences, etc.) is a plus.
* Must have the legal right to work in the United States