Staff Full-Stack Engineer — Customer Value + Performance Intelligence (Tech Lead)

BetterUp is a company focused on human transformation and innovative employer/employee relationships. They are seeking a driven full stack software engineer to build automation tooling and data pipelines that enhance customer insights and scale their Performance Intelligence capabilities.

Responsibilities:

• Architect and build automation tooling that reduces manual effort in insight generation and delivery by 75%, unlocking our ability to scale from 15–25 customers to hundreds
• Design and implement data pipelines that systematically process unstructured data (session recordings, chat logs, behavioral signals) through our Intelligence Layer
• Build self-service tooling that empowers cross-functional teams (PICs, Customer Value, Labs) to access and deliver insights without engineering bottlenecks
• Develop monitoring and observability systems to ensure insight quality and pipeline reliability at scale
• Collaborate with product, design, and data science to craft enterprise-grade experiences for Performance Intelligence features on our SPAs frontend (Ember, Lit) and backend services (Ruby, Elixir)
• Build robust APIs and interfaces that surface Intelligence Layer capabilities across multiple touchpoints—both in-product and through consultative tools
• Partner with ML Engineers and Data Scientists to operationalize unstructured data models and signal detection systems
• Strong desire to delight enterprise customers by building software that delivers actionable insights they can't get anywhere else
• Centralize and standardize data collection, transformation, and serving approaches across our analytics stack (Snowflake, dbt, Looker)
• Support reporting and analytics teams in delivering both internal and customer-facing business insights with consistency and reliability
• Build and maintain data quality checks, validation systems, and observability tooling that ensure insight accuracy across the full pipeline
• Partner with Data Platform on shared standards for data modeling, metric definition, and reporting architecture to ensure metrics consistency across teams
• Own your components during the entire lifecycle, from planning through development, deployment, and maintenance
• Build scalable and resilient systems using container technologies (Docker, K8s) and cloud infrastructure as code (AWS, Terraform)
• Design data infrastructure that handles growing volumes of session recordings, chat data, and behavioral signals while maintaining performance and cost efficiency