Senior Business Intelligence Engineer

Responsibilities

• Design, build, and maintain scalable data models, semantic layers, and data visualizations that serve business-critical reporting needs
• Partner with stakeholders across Engineering, Product, Finance, Marketing, and Operations to understand data requirements and translate them into reliable data solutions
• Own data quality, documentation, and governance practices for BI assets — ensuring dashboards and models are accurate, trustworthy, and maintainable
• Build and maintain dbt models to support consistent, reusable data definitions
• Leverage AI-assisted development tools to accelerate model development, dashboard scaffolding, and documentation — treating AI as a productivity multiplier while owning the analytical design and validation
• Develop and enforce best practices for data model development, such as naming conventions and testing standards
• Identify and resolve performance bottlenecks in queries, pipelines, and reporting layers
• Enable self-serve analytics by building machine-legible, intuitive data products that reduce ad hoc request volume
• Use data to surface insights proactively — not just respond to requests, but identify gaps and opportunities in the business
• Continuously evaluate and adopt emerging AI tooling to improve team velocity — contribute to defining how the BI team integrates AI into its standard workflows
• Contribute to the broader data team's roadmap, tooling decisions, and infrastructure

Requirements

• Demonstrated experience designing and delivering production-grade solutions in a complex, high-scale data environment
• Deep proficiency in SQL and data modeling — ability to read, validate, and direct complex queries
• Experience with a modern data stack (e.g. Snowflake/Databricks, dbt, Sigma/Looker, etc.)
• Strong ability to work directly with stakeholders — translating ambiguous business questions into clear, scoped data solutions
• Track record of building data products that are adopted and trusted by non-technical users
• Demonstrated experience building with AI tools (Claude, Codex, Copilot, Cursor, or similar) — active integration into daily analytical and engineering workflows

Nice to Have

• Experience in fintech, payments, lending, or regulated financial environments
• Familiarity with data orchestration tools (e.g., Airflow)
• Experience building or scaling BI infrastructure in a high-growth startup environment
• Experience defining or implementing AI-augmented analytics workflows at a team level
• Familiarity with agentic AI patterns (MCP, tool-use, context management) and how they apply to data workflows
• Exposure to Python or other scripting languages for data transformation or automation
• Track record of establishing BI governance or data quality frameworks from the ground up

Compensation & Benefits

• Competitive compensation and equity packages
• Leading configured work computers of your choice
• Flexible paid time off
• Fully covered, high-quality healthcare, including fully covered dependent coverage
• Additional health coverage includes access to One Medical and the option to enroll in an FSA
• 20 weeks of paid parental leave for the primary caregiver and 8 weeks for all new parents
• Access to industry-leading technology across all of our business units