Chartbeat’s 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, Chartbeat’s 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, we’re 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, we’ll 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.

The Team 

We are 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. 

Responsibilities

• Design, implementation, and support of large-scale data processing pipelines and microservices using Kubernetes, Spark, Kafka, and ElasticSearch, among other technologies
• Programming in Python and sometimes Scala, and Java
• Engineering mentorship through collaborative planning, design, and development
• Owning mission-critical software systems and working with Product Management and your teammates to define and execute on the future vision for the related product surface areas
• Participation in the backend team on-call rotation

About You

• 5 years of experience as a member of the technical staff at a data-intensive engineering company
• Track record of having made significant contributions to large-scale engineering projects
• Significant Spark development and performance optimization experience
• Advanced Python skillset and, ideally, some experience with either Scala or Java
• Experience working on customer-facing products, ideally in enterprise SaaS
• Bias toward collaborative working styles (e.g. XP/pairing or mob programming)
• Some experience with large-scale distributed datastores such as ElasticSearch, Flink, or similar
• Hands-on experience with relational databases such as MySQL and/or Postgres
• Passion and enthusiasm about writing well-thought-out code
• Demonstrable track record of having quickly mastered new technologies
• The ability to prioritize tasks, work independently, and respond to emergent issues accordingly
• Good intuition for design decisions supporting system uptime and performance
• Strong interpersonal communication skills