Data Analyst

About the role

Central Health is looking for a Data Analyst to join a collaborative analytics team that includes data analysts, epidemiologists, biostatisticians, and data scientists. In this position, you will support business intelligence, performance measurement, clinical analytics, and operational reporting across the organization.

Reporting to the Analytics Quality Manager, you will work with large healthcare datasets spanning EHR, clinical, financial, and enrollment sources. The role also includes acting as an Epic reporting specialist for both front-end and back-end reporting needs, helping design and verify datamarts, performance dashboards, and other reporting tools that support an integrated network of physicians, safety net providers, and hospitals focused on patient-centered, equitable, data-driven care.

Key responsibilities

• Build, manage, and refine complex SQL and/or Python queries to pull, combine, and summarize data from multiple systems, starting in SQL Server and later in Snowflake.
• Create, validate, and maintain reports, dashboards, and visual analytics in tools such as Power BI and Tableau for stakeholder communication.
• Interpret trends, relationships, and unusual data patterns, then convert those findings into practical recommendations for business, operational, and clinical teams.
• Work with operational, business, and clinical partners to define metrics, KPIs, and performance measures, and document the business rules and transformation logic behind them.
• Turn complex datasets into clear visual stories that surface trends, opportunities, and improvement areas.
• Check data accuracy through validation, reconciliation, and spot testing, especially for information moved from on-premise systems to cloud environments.
• Support automated data pipelines and quality controls in partnership with data engineering teams.
• Use SQL and Python for querying, modeling, staging, and automating reporting workflows.
• Develop reports and dashboards within Epic EHR and Power BI.
• Use Epic Clarity and Caboodle as primary data sources and help ensure consistency and accuracy across reporting layers.
• Assist in building and validating analytic datasets in Epic Caboodle for enterprise reporting and population health use cases.
• Help produce data dictionaries, metadata documentation, and validation procedures.
• Investigate and resolve data issues, anomalies, and irregularities.
• Contribute to stronger data quality and analytics by improving processes and automating repetitive manual tasks.
• Partner with Data Engineering, Integration, and Governance teams to preserve data definitions, lineage, and access controls.
• Become a subject matter expert on Central Health data sources and applications.
• Carry out other duties as assigned.

Requirements

• A background in Finance, Mathematics, Economics, Statistics, Actuarial Science, Computer Science, Engineering, or a similar quantitative field is expected; relevant hands-on healthcare data analysis experience may be accepted in place of a specific degree discipline.
• At least 2 years of experience in healthcare, statistics, experimental research, data science, reporting and analytics, economics, or public health.
• At least 1 year of intermediate-to-advanced SQL experience, preferably with T-SQL, plus Python scripting experience.
• At least 1 year of report development in Epic EMR using tools such as Clarity, Caboodle, SlicerDicer, Reporting Workbench, and Radar is preferred.
• Familiarity with healthcare claims processing, including billing codes, is preferred.
• Experience with statistical analysis tools such as SAS, R, or Python is preferred.
• At least 1 year of experience using Power BI or Tableau is required.

Additional information

This is a full-time, onsite position based in Austin, Texas. The role is centered on healthcare analytics and reporting, with a strong emphasis on Epic EHR data, cloud migration validation, dashboard development, and collaboration across data, governance, integration, and clinical teams.

The position also requires contributing to enterprise reporting and population health initiatives, documenting data standards, and supporting continuous improvement efforts through automation and quality controls.