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Healthcare Data Modeling Jobs (NOW HIRING)

DRC Systems

Technical Lead - Data Analysis

Boston, MA · Remote

$50 - $54/hr

... models, write complex SQL, and build performant analytics pipelines. * Data Visualization & Storytelling - Ability to translate complex healthcare data into actionable insights using dashboards and ...

ClinDCast LLC

Healthcare Domain SME

Roslindale, MA · Remote

Job Details: o Experience: 10+ years in healthcare data modeling, ETL, reporting related to EHR systems, EHR data related certifications or experience from one or two of the following EHR's is ...

AArete

Healthcare Data Developer

Chicago, IL · On-site

$90K - $120K/yr

Healthcare Data Developer AArete is one-of-a-kind when it comes to consulting firm culture We're a global, innovative management and technology consulting firm with offices in the U.S. and India. Our ...

Oxbridge Health

Data Integration Lead

Norwalk, CT · On-site

... healthcare partners. You will define and manage external data contracts, maintain partner-specific file and API specifications, translate external data into Oxbridge's canonical data model, and ...

RA Capital Management, LLC

Data Engineer

Boston, MA

$124K - $149K/yr

This role goes beyond traditional ETL. You will work on healthcare data pipelines and contribute to AI-driven data access layers where large language models translate user intent into structured ...

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Healthcare Data Modeling information

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$58

$83

How much do healthcare data modeling jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for healthcare data modeling in the United States is $58.71, according to ZipRecruiter salary data. Most workers in this role earn between $52.64 and $68.27 per hour, depending on experience, location, and employer.

What is healthcare data modeling?

Healthcare data modeling is the process of designing and structuring data systems to accurately represent, organize, and analyze healthcare information. This involves creating conceptual, logical, and physical models to ensure that data from sources like electronic health records, billing systems, and clinical databases can be integrated and used effectively. Effective data modeling helps healthcare organizations improve patient care, streamline operations, and comply with regulatory requirements by making data more accessible and meaningful for analysis and decision-making.

What are the key skills and qualifications needed to thrive as a healthcare data modeler?

To thrive as a Healthcare Data Modeler, you need expertise in data modeling concepts, healthcare data standards, and a background in computer science, information systems, or a related field. Proficiency with tools like SQL, ERwin, UML, and knowledge of HL7/FHIR standards is typically required, and certifications in data management or healthcare informatics are beneficial. Strong analytical thinking, attention to detail, and effective communication skills help in interpreting complex data requirements and collaborating with diverse stakeholders. These capabilities are crucial for ensuring accurate, interoperable healthcare data solutions that support clinical decision-making and regulatory compliance.

What are some common challenges faced by professionals in healthcare data modeling, and how can they be addressed?

Healthcare data modeling professionals often encounter challenges such as integrating data from diverse sources, ensuring data privacy, and dealing with incomplete or inconsistent datasets. Addressing these issues typically involves collaborating closely with IT, clinical, and compliance teams to standardize data formats and adhere to regulatory requirements like HIPAA. Regular communication with stakeholders and ongoing training in the latest data management tools can also help overcome these obstacles, ensuring that data models remain accurate and actionable for healthcare decision-making.

What is the difference between Healthcare Data Modeling vs Healthcare Data Analysis?

AspectHealthcare Data ModelingHealthcare Data Analysis
Primary FocusDesigning data structures and models for healthcare data systemsInterpreting and analyzing healthcare data to derive insights
Skills & CertificationsData modeling, database design, SQL, healthcare informaticsStatistical analysis, data visualization, SQL, healthcare analytics tools
Work EnvironmentHealthcare IT teams, data warehouses, EHR systemsResearch teams, healthcare organizations, analytics departments
Industry UsageDeveloping healthcare data infrastructureImproving patient outcomes through data insights

Healthcare Data Modeling focuses on creating the structure for healthcare data systems, ensuring data is stored efficiently and accurately. Healthcare Data Analysis involves examining healthcare data to identify trends and support decision-making. Both roles are essential in healthcare IT but serve different purposes within the data lifecycle.

What other helpful pages are available for Healthcare Data Modeling?

Other pages related to Healthcare Data Modeling:

Infographic showing various Healthcare Data Modeling job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $122,123 per year, or $58.7 per hour.

Technical Lead - Data Analysis

Boston, MA • Remote

DRC Systems
See more jobs at DRC Systemsexternal

$50 - $54/hr

Contractor

Re-posted 23 days ago

Job description

Title – Technical Lead – Data Analysis
Location – Boston, MA - Remote
JD - Key Skills

  • Advanced SQL & Data Modeling – Proven ability to design robust data models, write complex SQL, and build performant analytics pipelines.
  • Data Visualization & Storytelling – Ability to translate complex healthcare data into actionable insights using dashboards and stakeholder-ready visualizations.
  • Healthcare Analytics & Value-Based Care Expertise – Strong hands-on experience with claims and clinical data, value-based care metrics, and healthcare quality measures.

Must Have Skills

  • Healthcare Data Experience
    • 5+ years of hands-on experience working with healthcare data
    • Deep expertise in claims and/or clinical data
    • Strong understanding of medical economics, risk adjustment, quality measures, and population health analytics
  • Value-Based Care
    • Minimum 2+ years of experience supporting value-based care use cases
    • Ability to act as a Value-Based Care SME in internal and client-facing discussions
  • Technical & Analytics Skills
    • Advanced SQL (complex joins, window functions, performance tuning)
    • Strong data modeling skills to support analytics and BI developers
    • Experience creating custom tables, views, and stored procedures (preferably in AWS Redshift)
    • Ability to support ad hoc analytics and complex customer requests
  • Cloud & BI Tools
    • Hands-on experience with AWS data stack: Redshift, Athena, S3
    • Experience building and delivering dashboards using Amazon QuickSight
  • Client & Stakeholder Engagement
    • Comfortable engaging directly with healthcare customers
    • Strong ability to translate business and value-based goals into actionable analytics deliverables
    • Experience presenting insights clearly to technical and non-technical stakeholders Good to Have Skills
  • Modern Data & Analytics Tools
    • Experience with dbt, Snowflake, or Looker
    • Familiarity with data pipelines and SaaS-scale analytics platforms
  • Programming & Automation
    • Ability to write and troubleshoot Python for data analysis or automation
    • Familiarity with GitHub and CI/CD tools such as Jenkins
  • Healthcare Interoperability
    • Understanding of FHIR or other healthcare interoperability standards
  • AI & Advanced Analytics
    • Experience integrating or validating AI-powered coding or analytics tools
    • Exposure to model QA, validation, or analytics governance
  • Tooling & Collaboration
    • Experience using Jira and Confluence in an agile environment
  • Industry Exposure
    • Prior experience working at a healthcare data vendor, ACO/CIN, payer, or healthcare SaaS company
  • AWS Ecosystem
    • Broader exposure to AWS services beyond core analytics stack