Data Analyst
New
E
EnableCompHealthcare revenue cycle
United States - RemoteFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years of experience in data analysis, reporting, or working with relational databases required; 3 years of integrating Databricks, Power BI, and Claude Code
- Required Skills
- SQLMicrosoft Power BITableauMicrosoft ExcelPowerPointDatabricks
Requirements
- Bachelor’s degree in Analytics, Finance, Business, Computer Science, Healthcare Administration, or a related field.
- 5+ years of experience in data analysis, reporting, or working with relational databases.
- 3 years of experience integrating Databricks, Power BI, and Claude Code.
- Experience with the Databricks Data Intelligence Platform.
- Proficiency in writing SQL queries.
- Proficiency in Microsoft Excel and PowerPoint.
- Experience with statistical analysis or predictive modeling techniques.
- Familiarity with healthcare terminology such as CPT codes, DRG, claims, and inpatient/outpatient.
- Experience with BI tools such as Power BI, Tableau, or Qlik is preferred.
- 3–5 years of experience in healthcare, revenue cycle, or a SaaS environment is strongly preferred.
- Ability to communicate complex data insights clearly to audiences with varying levels of technical expertise.
- Strong attention to detail and focus on accuracy, validation, and quality.
Responsibilities
- Analyze large, complex datasets to identify trends, patterns, and actionable insights.
- Develop, maintain, and optimize reports, dashboards, and analytical models for operational and financial performance.
- Translate analytical findings into executive-ready summaries and presentations.
- Partner with stakeholders to understand business needs, define requirements, and deliver data-driven solutions.
- Query, transform, and prepare datasets using SQL and other tools.
- Build structured datasets by joining tables and validating data integrity.
- Validate analyses and perform quality checks to ensure accuracy and reliability.
- Document methodologies, assumptions, and processes.
- Identify root causes and recommend data-backed solutions and process improvements.
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