Full Stack Business Analyst

Summary

Join our team as a Full-Stack Business Analyst to enhance physician and patient quality of life through data-driven analyses and support data-driven decision-making across the organization.

Requirements

• 5+ years of experience in a business analyst, data analyst, or similar role, with a focus on full-stack data work
• Exceptional communication skills, with the ability to present complex data in a clear and concise manner to non-technical stakeholders
• 5+ years of experience driving change through analyses and actionable recommendations through organizations
• Proven Track record of gaining buy-in across the organization from executive to front-line management
• Excellent analytical, problem-solving, and critical-thinking skills
• Strong experience with data analysis tools (e.g., SQL, Python, R), data visualization tools (e.g., Looker, Tableau, Power BI), and data warehouses (e.g., Snowflake, BigQuery) operating on large data sets
• Applies pragmatic approaches and use of tools with focus on delivering business outcomes
• Experience with data engineering tools (e.g., dbt) and data integration platforms (e.g., Fivetran)
• Familiarity with scripting languages (e.g., Python) for data manipulation and automation
• Knowledge of statistical analysis and predictive modeling techniques
• Hands-on experience with data extraction from various business systems (e.g., Salesforce, NetSuite, HubSpot, etc.)
• Proficient in building ETL pipelines and integrating data into data warehouses (e.g., Snowflake, Redshift, BigQuery)
• Expert in Excel and advanced knowledge of google sheets, including scripting

Responsibilities

• Partner with leaders of business functions across the organization to drive data-driven business decisions to achieve key company outcomes
• Build, then train stakeholders on how to use dashboards, reports, analysises to drive operational improvements and business outcomes
• Manage internal data warehouse instance (Snowflake) through data transformation and modeling tools (e.g., dbt), as well as manage data visualization tool (Looker)
• Evangelize data-driven decision-making and make data and tools accessible to any team member across the organization
• Develop consistent data modeling and representation standards that simplify maintenance and comprehension