Sr. Business Intelligence Engineer

We’re looking for a driven, passionate Senior Business Intelligence Engineer to join our Business Intelligence team. This role focuses heavily on connected device and software telemetry analytics, predictive modeling, system design, and workflow intelligence, while supporting the buildout of our Account 360 Medallion Architecture.

Our team operates on a mature two-week sprint cadence, and we prioritize speed-to-value and urgent execution—ensuring we push actionable, working models into our partners' hands quickly rather than developing in isolation. You will work within a strict 60/20/20 capacity model (Planned Work / Ad-Hoc / Protected Tech Debt Buffer) that protects your time to build robust, scalable predictive pipelines without getting buried in operational emergencies.

Design and construct the Account 360 Medallion Architecture, integrating and structuring complex datasets from SAP, Sales Force, connected device data and other enterprise systems to power predictive models.. Utilize advanced programming languages (Python, R) alongside advanced SQL to perform deep-dive statistical analysis, predictive modeling, segmentation, and scenario planning.

Build automated data enrichment pipelines that append firmographics, identify net-new prospects, and expand our database to drive system-sourced revenue. Prioritize speed-to-value by deploying simple, working versions of data products and algorithms quickly, iterating based on real-world stakeholder feedback. Actively participate in our team's cross-training framework, dedicating 4 hours per sprint to co-piloting tasks and sharing advanced analytical techniques with peers.

Manage your individual workload within our 10-point sprint capacity model, utilizing your protected 20% buffer time to continuously pay down tech debt and refactor legacy code. Analyze device telemetry, software usage patterns, feature adoption, and error logs to deliver actionable insights to R&D, Product Management, Sales, Marketing and Service teams.

Leverage Machine Learning, NLP, and process mining techniques to analyze customer interaction sequences, voice commands, and unique workflows to identify user friction and optimize product experience. Ability to travel up to 15% to collaborate with cross-functional teams and key stakeholders.