Axuall is a clinical workforce intelligence company that enables healthcare organizations to improve operational efficiency and strengthen clinical coverage. The Sr. Business Intelligence & Analytics Manager will lead data utilization across the business to drive measurable impact, overseeing data pipelines, models, and insights for internal decision-making and customer-facing value.
Responsibilities:
- Build, maintain, and extend data pipelines across product, CRM, and third-party sources to ensure reliable, scalable data access that power analytics across the business and for customers
- Own and manage the BI environment, including data models, transformation processes, and visualization tooling
- Translate Axuall’s data into actionable insights that drive product value, customer outcomes, and revenue growth
- Establish and enforce standards for data quality, consistency, and governance to ensure accuracy and trust in all analytics outputs
- Enable self-service analytics by maintaining a consistent, trusted data foundation that drives speed and confidence in decision-making
- Develop and support AI-driven data workflows that extract insights (e.g., sentiment, patterns) to inform product strategy and customer value realization
- Support business leaders to communicate internally and externally with data
Requirements:
- 4+ years of experience in analytics engineering or data engineering within a SaaS or data-driven environment
- Expert-level SQL and strong Python skills, with the ability to build and maintain scalable data models and pipelines
- Hands-on experience with dbt in a production environment (experience managing large model sets preferred)
- Strong data wrangling skills - comfort working with messy, real-world datasets
- Experience building customer-facing dashboards or reports, including presenting findings to executive and operational audiences
- Ability to translate data findings into clear, non-technical business narratives for executive and operational audiences
- Strong experience with BI and analytics tools (e.g., Omni, Sigma, Tableau, or Power BI), including building governed, self-service data layers
- Experience working with modern data warehouses (e.g., ClickHouse, BigQuery, Redshift, or similar)
- Experience with pipeline orchestration tools (e.g., Dagster, Airflow, Prefect, or similar)