Lead Business Intelligence Analyst

About the role 

CirrusMD is seeking a strategic Lead Business Intelligence Analyst with 5+ years of relevant analytics experience who thrives in deriving insights out of complex data. You are a bridge-builder and critical insights partner who demonstrates the value for CirrusMD, aligns business intent with technical execution, and fosters a culture of data-informed decision-making. You partner with teams across the entire organization and do not hesitate to get into the weeds to understand the data. This role will be instrumental in providing accurate and meaningful data and insights that will be used to pave the way for our path ahead.  

Location: This position may work remotely anywhere in the United States of America. 

What you’ll do (Essential Responsibilities) 

• Bridge the Gap: Act as the primary data partner to product, clinical, client success, finance, and engineering teams to align cross-functional initiatives and build a unified, data-informed organizational ecosystem. 

• Quantify Value: Architect robust measurement frameworks that transform product, clinical, and commercial initiatives into clearly defined performance metrics, directly demonstrating the economic value and ROI of CirrusMD’s solution to external stakeholders and clients 

• Data Lifecycle Ownership: Own the project data lifecycle - from initial ideation and feasibility assessment to building internal/client-facing reporting. 

• Semantic Layer Stewardship: Collaborate with engineers to define data structures and build out the Looker semantic layer to ensure high-trust, reusable data. 

• Insight Generation: Transform complex datasets into actionable insights that influence the strategic direction of the organization. 

• Performance Visibility & Delivery: Build and maintain high-impact visualization solutions and reporting frameworks that drive awareness and understanding of key performance metrics. 

• All other duties assigned. 

What you’ll bring (Qualifications) 

• Experience: 5+ years of relevant analytics experience 

• Strategic Partnership: Proven experience translating business requirements into technical execution for cross-functional stakeholders. 

• Technical Proficiency: Strong to advanced SQL skills; experience with Cloud Data Platforms (e.g., Snowflake) and BI reporting tools (e.g., Looker Cloud/On-Prem). 

• Data Modeling: Expert in building semantic layers (LookML), managing version control via GitHub, and applying data architecture best practices to ensure scalable, high-performance reporting environments. 

• Lifecycle Management: Proven ability to manage the full data lifecycle, from greenfield modeling to refactoring and optimizing legacy technical debt. 

• Communication: Exceptional bi-directional communication skills that allow you to distill complex technical topics for non-technical stakeholders while also collaborating effectively with technical counterparts. 

• Autonomy & Prioritization: Proven ability to manage competing priorities, knowing when to dive deep and when to zoom out to meet deadlines. 

• Data Governance & Client Delivery: Experience fulfilling complex, client-facing data requests while maintaining clear boundaries around data governance. You are highly adept at balancing stakeholder accommodation with a strict adherence to established organizational standards.  

• Integrity: Experience owning high-integrity data processes (e.g., billing, invoicing, or clinical reporting) where accuracy is non-negotiable. 

• Analytical Rigor: Knowledge and application of statistical methods and concepts such as incorporating confidence intervals, hypothesis testing, sentiment analysis, and anomaly detection. 

Preferred Qualifications

• Advanced Analytics: Experience with data transformation tools (dbt, Airflow) and the ability to leverage toolsets (Python/R) for analysis beyond standard SQL. 

• Healthcare Domain Expertise: Deep understanding of HIPAA/FedRAMP compliance, PII/PHI handling, and clinical metrics (HEDIS/NCQA/NQF). 

• CDP Experience: Knowledge of event-based tracking and Customer Data Platforms (e.g., Segment). 

• Systems Thinking: A holistic understanding of modern data stacks, infrastructure dependencies, and how upstream engineering impacts downstream consumption.  

• AI Fluency: Experience implementing AI-driven BI capabilities (such as Natural Language Querying or Looker Conversational Analytics) to democratize data access and enable intuitive, self-service exploration for business users 

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