Data Engineering - Tech Lead

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 a 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

• As a Data Engineering Tech Lead, you will be a technical leader in the design, development, scaling, and maintenance of our core intelligence product pipelines, data stores, query engines, and internal APIs.
• You will be managing a team of two to three Engineers, help plan and run their scrum, lead technical architecture and design sessions, contribute and review code.
• You will have an impact on the architectural vision and prioritization of technical projects across the broader engineering organization. 
• You will participate in an engineering on call rotation to monitor and maintain the health of our production systems.

About You

• 8+ years experience as a senior data engineer
• Strong experience working with production level python
• Strong experience working with Spark, PySpark or similar 
• Experience working on end-user products, ideally in enterprise SaaS 
• Experience working with microservices in Kubernetes 
• Proven track record tech leading large-scale engineering projects
• Experience with large-scale distributed datastores such as ElasticSearch
• Experience working with and building distributed systems (e.g. Consul, Zookeeper, Kafka)

The salary range for this role is $185k-200k