Senior Business Intelligence Engineer
About the role
Own the design, development, and delivery of scalable data models, semantic layers, and dashboards that serve business-critical reporting across Imprint. Partner directly with Engineering, Product, Finance, Marketing, and Operations to translate ambiguous business questions into reliable, scoped data solutions. Build and maintain dbt models that establish consistent, reusable data definitions and reduce ad hoc request volume through self-serve analytics infrastructure. Leverage AI-assisted development tools (Claude, Cursor, Copilot) to accelerate implementation, from SQL generation and model scaffolding to automated documentation, while owning the analytical design and validation. Own data quality, governance, and documentation practices for BI assets, ensuring dashboards and models are accurate, trustworthy, and discoverable. Surface insights proactively by identifying gaps and opportunities in the business, not just responding to inbound requests. Evaluate and adopt emerging AI tooling to improve team velocity, contributing to how the BI team integrates AI into its standard workflows.
Responsibilities
- Design and deliver production-grade data solutions in a complex, high-scale environment
- Translate ambiguous business questions into clear, scoped data products that non-technical users actually adopt and trust
- Work directly with stakeholders to define what "good" looks like
- Leverage AI-assisted development tools (Claude, Cursor, Copilot) to accelerate implementation, from SQL generation and model scaffolding to automated documentation
- Evaluate and adopt emerging AI tooling to improve team velocity
Requirements
- Proven experience designing and delivering production-grade data solutions in a complex, high-scale environment
- Deep SQL proficiency and strong data modeling fundamentals; the ability to read, validate, and direct complex queries matters more than raw writing speed in an AI-assisted workflow
- Experience with a modern data stack (e.g., Snowflake or Databricks, dbt, Sigma or Looker)
- Strong ability to work directly with stakeholders, translating ambiguous business questions into clear, scoped data products that non-technical users actually adopt and trust
- Active experience building with AI tools (Claude, Codex, Copilot, Cursor, or similar) integrated into daily analytical and engineering workflows, not just awareness
- Comfort operating in a fast-moving startup environment where you own projects end-to-end, prioritize based on business impact, and move fluidly between writing production SQL and sitting with stakeholders to define what "good" looks like
Qualifications
- Experience in fintech, payments, lending, or regulated financial environments
- Experience building or scaling BI infrastructure at a high-growth startup, including governance and data quality frameworks from scratch
- Familiarity with data orchestration tools (e.g., Airflow) and Python or other scripting languages for transformation and automation
- Experience defining AI-augmented analytics workflows at a team level: AI-assisted code review, automated documentation, prompt-driven data exploration, or agentic patterns like MCP and tool-use applied to data workflows
Skills
- SQL as the primary language, with Python for transformation and automation
- AWS infrastructure
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, stemming from our philosophy that we should invest in resources for our team that foster innovation, optimization, and productivity