Business Intelligence Engineers (BIEs) support data-driven decision-making across the business through analytics, data engineering, and insight generation. The team is seeking a Senior BIE to lead the design of scalable BI systems that enable self-service analytics and high-impact insights.
This role owns the architecture and long-term strategy for the BI ecosystem. The focus is on building platforms - not just reports - that make data accessible, reliable, and easy to use. Responsibilities include developing automated data pipelines, advanced analytical models, and intuitive visualizations that influence how teams operate.
A strong Senior BIE builds deep business and domain knowledge. Success in this role comes from understanding how the business works, diving into root causes, and using that context to deliver insights that matter. The role requires thinking like a product owner by anticipating needs, identifying gaps, and building solutions that scale beyond individual requests.
The role operates at the intersection of data engineering, analytics, and emerging AI capabilities, eliminating manual processes, reducing bottlenecks, and unlocking new insights. Work includes writing high-quality, maintainable code using SQL (required), Python, R, or similar languages.
Clear and influential communication is critical. Findings must be shared using the most effective format - dashboards, written narratives, or presentations so that insights are understood and acted on.
This is a high-visibility role due to the critical tools maintained and the broad network impact of the analysis. The ideal candidate is self-directed, comfortable with ambiguity, and motivated by solving complex problems while continuously raising the bar.

Key job responsibilities
• Lead design, implementation, and delivery of BI solutions for complex, ambiguous problem spaces, creating new solutions or revising existing ones
• Think architecturally and take long-term view of team solutions by building reusable, scalable solutions that minimize ad-hoc requests and enable self-service analytics
• Identify and implement automation opportunities to improve team efficiency and reduce manual effort
• Design and implement robust reporting solutions ensuring accuracy, timeliness, accessibility, and actionability
• Build and manage KPIs; monitor existing metrics, build new metrics, and partner with internal teams to identify improvement opportunities
• Retrieve and analyze large datasets using SQL, Python, and other data management systems to build scalable, extensible solutions that are easy to maintain
• Design, build, and maintain ETL pipelines to ensure reliable data flow from source systems to analytics platforms
• Adapt quickly to changing business environments and priorities, demonstrating versatility across different problem domains and technical stacks
• Influence team's technical and business strategy through insightful contributions, making sound trade-offs between complexity and simplicity
• Stay current with emerging AI tools and technologies to unlock new analytical and optimization capabilities
• Drive BI engineering best practices including operational excellence, code reviews, syntax/naming conventions, metric definitions, and alarms