Software Engineer, Analytics Platform

About Outreach   Outreach, founded in 2014, is the only complete agentic AI platform for revenue teams. Outreach infuses agentic AI, conversation intelligence, and assistive AI to power hundreds of use cases across revenue motions. From new logo prospecting to expansions, deal acceleration, driving retention, and forecasting, Outreach AI automates workflows and frees sellers to focus on more strategic conversations and actions. Revenue leaders benefit from connected account visibility, performance insights, and higher forecasting accuracy across every GTM team. World leading enterprise organizations use Outreach to power their revenue teams, including Databricks, SAP, Siemens, and Verizon to name a few.  The Role   Today, data is everywhere, but only those who truly know how to use it effectively will succeed. Outreach believes there are large swaths of value still locked in sales operations data and we are putting an effort behind building out the best team to help Outreach and our customers succeed through the use of data.  As our customer base grows, the desire for more insights, better coaching, and improvements in efficiencies outpace the supply. The Analytics team is focused on Analytics, Coaching Insights and Workflow optimization. This is a critical role that has a unique chance to build outcome-driven reports and analytics to guide our customers, improve their productivity and have a bigger impact on their revenue growth.  About the Team  This is a growing team within Outreach. This role would set the bar for engineering and operational excellence, team culture, business impact and hiring standards. Our customer base is yearning for more insights and this team will have a large impact on revenue, operational costs, and coaching efficiencies.  This team will span multiple functions including machine learning, frontend, backend engineering and data engineering. The Analytics team will work closely with Data Science to leverage models for optimization, as well as develop their own models, the Data Platform team to shape data efficiently, the Product Management and User Interface Designers to surface data in an effective way.