Why Hearst Magazines?
Hearst Magazines is one of the largest publishers in the world, with more than 25 brands, including Cosmopolitan, ELLE, Esquire, Good Housekeeping, Harper's BAZAAR, Popular Mechanics, and O the Oprah Magazine. We reach more than 150 million people every month in the United States alone.
But we're more than just our magazines. We engage our audience across all mediums and channels - print, digital, video and social – with sophisticated content creation, distribution and data capabilities. We create, package and sell products with cutting-edge technology and proprietary platforms. Together, we are reinventing media for the 21st century.
Hearst's Media Platforms division is Hearst's internal product, technology and design group, which spans both CDS Global and Hearst Magazines (www. www.mediaplatforms.hearst.com). Media Platforms is looking for an engineer to build scalable and resilient backend systems. You will be working on services that power online magazines that reach over 150 million people . And that's just the United States, our global reach is even larger. At Media Platforms, our technology, tools, services and solutions touch hundreds of millions of lives by driving experiences, and growing businesses. Our team of engineers, product managers, data scientists and designers build a suite of products to lead the way in shaping and managing the future of publishing.
Things you will do
• Design and build highly scalable and resilient backend systems that are micro-services based
• Analyze & solve difficult problems across the stack
• Build data pipelines that effectively ingest and provide access to data that will be leveraged by technology, business intelligence, and advertising operations teams.
• Conduct design and code reviews
• Analyze and improve efficiency, scalability, and stability of various system resources
Your background and skills should include
• Bachelor's degree in Computer Science or equivalent practical experience. Master's degree a plus
• 3+ years experience and a track record in building and scaling production-grade distributed systems that are stable, resilient, and performant
• Deep knowledge of data stores and related topics - both NoSQL and RDBMS - eg. Redis, Memcached, MySQL, PostgreSQL, etc
• A thorough understanding of distributed systems with an eye to catch performance bottlenecks from system metrics
• Experience working with a container ecosystem (eg. Docker, Kubernetes)
• Knowledge with object-oriented or functional programming skills. Python preferred.
• Experience with AWS, especially EC2, RDS and SQS
• Experience with traditional agile methodology.
We would be thrilled if you have
• Knowledge of Big Data technologies such as Spark, Kafka, and Apache Solr
• Experience working with Airflow
• Experience with BI tools like Looker and Tableau.
• Knowledge of Natural Language Processing (NLP) and/or Machine Learning(ML)
Jobcode: Reference SBJ-r7e1mk-3-215-177-171-42 in your application.