Business Intelligence Engineer

Tempus is seeking a Business Intelligence (BI) Engineer to support reporting, analytics, and data solutions that help teams make informed, data-driven decisions. This role partners with business stakeholders, data engineering, product, and operations teams to turn business needs into dashboards, metrics, and analytical datasets.

The BI Engineer will help develop reporting solutions, improve data accessibility, and contribute to a strong data culture across the organization.

Key Responsibilities

• Build and maintain BI dashboards, reports, and self-service analytics tools for cross-functional stakeholders.

• Partner with business teams to define KPIs, reporting requirements, and success metrics.

• Support the development and maintenance of curated data models for consistent reporting.

• Write SQL and data transformation logic to prepare data for analytics use cases.

• Collaborate with data engineers and platform teams to support business reporting needs.

• Validate data accuracy and troubleshoot discrepancies in reports and dashboards.

• Improve documentation, metric definitions, and data governance practices for analytics assets.

• Support ad hoc analysis and help stakeholders interpret trends and operational insights.

• Identify opportunities to automate recurring reporting.

• Contribute to BI best practices, visualization standards, and data quality monitoring.

Bachelor’s degree in a quantitative or technical field such as Computer Science, Information Systems, Statistics, Mathematics, Economics, or a related discipline, or equivalent practical experience.

• Experience in business intelligence, analytics, data analytics, or a similar role.

• Strong SQL skills and experience working with relational databases and structured datasets.

• Experience building dashboards and reports in BI tools such as Tableau, Looker, Power BI, or similar platforms.

• Ability to work with business stakeholders to translate requirements into reporting solutions.

• Familiarity with data modeling concepts and metric definitions.

• Strong attention to detail and commitment to data accuracy and quality.

• Effective communication skills with both technical and non-technical audiences.

Preferred

• Experience working in healthcare, life sciences, diagnostics, or other regulated environments.

• Familiarity with data transformation tools such as dbt or similar frameworks.

• Experience with Python, R, or another scripting language for analysis or automation.

• Understanding of data warehousing concepts and modern analytics stacks.

• Exposure to operational analytics or product analytics.

• Experience documenting KPIs, business logic, and analytics definitions for shared use. CHI: $70,000-$90,000