About the job Senior Software Engineer (Backend)

Chartbeats intuitive and powerful software has long empowered media brands to use their own data to build loyal audiences across desktop, social, and mobile platforms. With easy-to-use real-time and historical analytics, in-page optimization and testing tools, and unique insights into audience engagement, Chartbeats products bring value to editorial, product, and business teams. Earlier this year, Chartbeat joined forces with Tubular, the leader in global social video intelligence and measurement. Tubular provides a unified view of the shifting values and interests of audiences across YouTube, Instagram, Facebook, Twitch, and more. Together, were expanding the ecosystem of insights we provide to enterprise content creators who are developing audiences and revenue streams across channels. By joining two comprehensive network-level datasets, well help our partners understand and measure a larger proportion of audience interactions and, in turn, make smarter decisions that grow reach and revenue. We now serve more than 1,000 brands globally, including influential content publishers like The New York Times, the BBC, ESPN, Gannett, Vox, BuzzFeed, Paramount, WB, Mediahuis, Hearst, McClatchy, and GQ.

We are an international team focused on large-scale data systems who work with best in class technologies such as Spark, Kubernetes, ElasticSearch and Python. We make an impact by working within a close-knit team on core customer-facing analytics and search products.

• Design, implementation, and support of large-scale data processing pipelines and microservices using Kubernetes, Spark, Kafka, and ElasticSearch, among other technologies
• Programming in Python
• Owning mission-critical software systems and working with your team to execute on the future vision for the related product surface areas
• Participation in on-call rotation

• At least 5 years of experience as a software engineer working with Backend systems
• Strong industry experience with Python
• Hands on experience with most of the following or similar technologies: MySQL, ElasticSearch, Spark, Kafka
• Experience working with large-scale data in production systems and collaborating with Data Scientists or Machine Learning Engineers.
• Familiarity with supervised machine learning pipelines and metrics highly desired