Sr. Business Intelligence Engineer

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. Requirements:

• 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.

• Bachelor’s degree in a specific technical field (Computer Science, Math, Statistics, Data Science) or a business degree with a highly technical and quantitative focus.
• Minimum of 3-5 years of related industry experience in business intelligence, advanced analytics, or data modeling.
• Strong expertise in SQL is required; ability to write complex queries, manipulate large datasets, and engineer data features.
• Proficiency in at least one advanced analytical programming language (Python or R) and associated statistical modeling libraries (e.g., pandas, scikit-learn, statsmodels).
• Hands-on experience developing Machine Learning models (classification, regression, clustering, time-series forecasting) to solve real-world hardware, software, or business problems.
• Creative thinker with active humility and excellent communication skills, capable of explaining complex statistical concepts to non-technical stakeholders.
• Proactive, positive, self-starter attitude with a servant-leadership mindset to empower other teams to reach their revenue goals.