Healthcare Data Analyst Jobs
Healthcare Data Analyst jobs are open across hospital systems, health insurance, pharmaceutical companies, and public health agencies, at every level from entry-level to senior and lead, with specializations in clinical analytics, population health, and revenue cycle analysis. Find a role that fits from the openings below and apply directly.
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ASSYST is seeking an experienced Senior Healthcare Data Engineer to lead system integration, programming automation, and data modernization initiatives for our Client in Austin TX (Hybrid)
The Senior Healthcare Data Engineer leads the effort to evaluate and specify business requirements for electronic initial case report (eICR) ingestion, design auto-population mechanisms for registry fields, streamline the clinical review triage process, and construct operational dashboards. Shall be working closely with epidemiologists, clinical abstractors, and database architects, the developer will build automated, reliable workflows to extract, validate, and incorporate complex clinical and public health data into active surveillance workflows.
Key Responsibilities:
- Conduct an in-depth needs assessment to determine system and functional requirements for TBIRDS to ingest incoming eICRs and auto-populate designated registry fields.
- Translate epidemiological and clinical surveillance workflows into concrete technical specifications, data dictionaries, and architectural recommendations.
- Produce formal System Requirements Documents (SRD) and comprehensive integration runbooks to ensure long-term solution sustainability
- Design, build, test, and maintain automated data pipelines using SAS, Python, R, or SQL to extract, ingest, and process high-volume electronic health record (EHR) data feeds.
- Create automated rules for deterministic and probabilistic record linkage, entity deduplication, and integration across relational databases.
- Automate the clinical review workflow to triage and route incoming case alerts, minimizing manual abstraction lag.
- Build, configure, and maintain interactive operational dashboards tracking eCR ingestion volumes, data completeness, processing bottlenecks, and transformation error rates.
- Present actionable system and surveillance metrics to branch leadership, epidemiologists, and technical collaborators.
- Establish unit, integration, and regression testing frameworks to validate pipeline reliability, data completeness, and standardization.
- Ensure transformations strictly preserve semantic meaning across clinical terminology sets and interoperability standards.
- Debug script issues, address parsing anomalies, and continuously optimize data ingestion throughput.
- Maintain end-to-end documentation for all scripts, schemas, data flows, and automated ETL procedures.
- Interface between epidemiological researchers, IT infrastructure teams, and external healthcare reporting partners to ensure aligned system modernization.
Qualifications & Skill Requirements
- 8+ Years in Scripting & Statistical Programming, Hands-on development, testing, maintenance, and troubleshooting using SAS, Python, R, or comparable enterprise data languages.
- 8+ Years in System Integration & Automation, Proven track record designing automated interoperability workflows, data exchange routines, and dashboard solutions.
- 8+ Years in Health & Database Systems, Experience querying and managing complex structured or semi-structured healthcare, public health, or administrative datasets using relational databases (SQL).
- 8+ Years in System Requirements & Technical Analysis, Demonstrated ability to evaluate business and programmatic needs and translate them into formal technical specifications and system reports.
- 8+ Years in Data Validation & Quality Assurance, Methodological testing, auditing, and verification of automated data integration pipelines.
- 8+ Years in Technical Documentation & Communication, Strong documentation habits alongside demonstrated ability to explain complex technical concepts to non-technical and clinical staff.
Preferred Qualifications
- 2+ Years in Healthcare Interoperability & Messaging, Direct experience handling electronic case reporting (eCR / eICR), Health Information Exchanges (HIE), Electronic Health Records (EHR), and standards such as HL7 (v2/v3), CDA, HL7 FHIR, XML, or JSON.
- 2+ Years in Clinical Terminology, Familiarity working with standardized clinical classifications such as SNOMED CT, LOINC, and ICD-10.
- 2+ Years in Public Health & Registry Systems, Experience working with state public health registries, disease surveillance systems, data linkage/matching methods, and production-grade ETL pipelines.
ASSYST is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, disability, military status, national origin or any other characteristic protected under federal, state, or applicable local law
ASSYST is seeking an experienced Senior Healthcare Data Engineer to lead system integration, programming automation, and data modernization initiatives for our Client in Austin TX (Hybrid)
The Senior Healthcare Data Engineer leads the effort to evaluate and specify business requirements for electronic initial case report (eICR) ingestion, design auto-population mechanisms for registry fields, streamline the clinical review triage process, and construct operational dashboards. Shall be working closely with epidemiologists, clinical abstractors, and database architects, the developer will build automated, reliable workflows to extract, validate, and incorporate complex clinical and public health data into active surveillance workflows.
Key Responsibilities:
- Conduct an in-depth needs assessment to determine system and functional requirements for TBIRDS to ingest incoming eICRs and auto-populate designated registry fields.
- Translate epidemiological and clinical surveillance workflows into concrete technical specifications, data dictionaries, and architectural recommendations.
- Produce formal System Requirements Documents (SRD) and comprehensive integration runbooks to ensure long-term solution sustainability
- Design, build, test, and maintain automated data pipelines using SAS, Python, R, or SQL to extract, ingest, and process high-volume electronic health record (EHR) data feeds.
- Create automated rules for deterministic and probabilistic record linkage, entity deduplication, and integration across relational databases.
- Automate the clinical review workflow to triage and route incoming case alerts, minimizing manual abstraction lag.
- Build, configure, and maintain interactive operational dashboards tracking eCR ingestion volumes, data completeness, processing bottlenecks, and transformation error rates.
- Present actionable system and surveillance metrics to branch leadership, epidemiologists, and technical collaborators.
- Establish unit, integration, and regression testing frameworks to validate pipeline reliability, data completeness, and standardization.
- Ensure transformations strictly preserve semantic meaning across clinical terminology sets and interoperability standards.
- Debug script issues, address parsing anomalies, and continuously optimize data ingestion throughput.
- Maintain end-to-end documentation for all scripts, schemas, data flows, and automated ETL procedures.
- Interface between epidemiological researchers, IT infrastructure teams, and external healthcare reporting partners to ensure aligned system modernization.
Qualifications & Skill Requirements
- 8+ Years in Scripting & Statistical Programming, Hands-on development, testing, maintenance, and troubleshooting using SAS, Python, R, or comparable enterprise data languages.
- 8+ Years in System Integration & Automation, Proven track record designing automated interoperability workflows, data exchange routines, and dashboard solutions.
- 8+ Years in Health & Database Systems, Experience querying and managing complex structured or semi-structured healthcare, public health, or administrative datasets using relational databases (SQL).
- 8+ Years in System Requirements & Technical Analysis, Demonstrated ability to evaluate business and programmatic needs and translate them into formal technical specifications and system reports.
- 8+ Years in Data Validation & Quality Assurance, Methodological testing, auditing, and verification of automated data integration pipelines.
- 8+ Years in Technical Documentation & Communication, Strong documentation habits alongside demonstrated ability to explain complex technical concepts to non-technical and clinical staff.
Preferred Qualifications
- 2+ Years in Healthcare Interoperability & Messaging, Direct experience handling electronic case reporting (eCR / eICR), Health Information Exchanges (HIE), Electronic Health Records (EHR), and standards such as HL7 (v2/v3), CDA, HL7 FHIR, XML, or JSON.
- 2+ Years in Clinical Terminology, Familiarity working with standardized clinical classifications such as SNOMED CT, LOINC, and ICD-10.
- 2+ Years in Public Health & Registry Systems, Experience working with state public health registries, disease surveillance systems, data linkage/matching methods, and production-grade ETL pipelines.
ASSYST is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, disability, military status, national origin or any other characteristic protected under federal, state, or applicable local law
Healthcare Data Analyst Jobs by Experience Level
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Who's Hiring
Top Industries Hiring
- Staffing & Recruiting
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What Employers Look For
The qualifications that appear most often in healthcare data analyst jobs.
- Proficiency in SQL for querying relational databases and clinical data warehouses
- Experience with data visualization tools such as Tableau, Power BI, or Qlik
- Familiarity with EHR systems including Epic, Cerner, or Meditech
- Bachelor's degree in health informatics, statistics, computer science, or a related field
- Knowledge of healthcare terminology, ICD-10 coding, and claims data structures
- Experience with Python or R for data manipulation and statistical analysis
Tips for Your Healthcare Data Analyst Job Search
Tailor your resume to the data stack
Healthcare data analyst job listings almost always name specific tools like SQL, Python, Tableau, or Epic. Mirror the exact tool names from each posting in your resume skills section so automated screening systems flag your application as a match.
Highlight HIPAA and data governance experience
Many hiring managers filter for candidates who understand protected health information handling. Call out any experience working with de-identified datasets, HIPAA-compliant pipelines, or audit-ready reporting processes directly in your work history bullets.
Build a portfolio around a clinical or claims dataset
Generic data projects won't differentiate you. Use a publicly available claims or public health dataset to build one end-to-end project showing data cleaning, analysis, and a dashboard. Link it in your resume so recruiters see domain-specific work immediately.
Apply early to roles that fit
Migrate Mate lists healthcare data analyst openings from across the United States in one place, so you can find roles that match your skills and apply directly to each listing.
Filter by EHR platform to narrow your search
Roles tied to Epic, Cerner, or Meditech require different technical fluency. Search for openings that match the EHR platform you know best so your application speaks directly to what the team uses day to day.
Prepare a SQL or analytics walkthrough for interviews
Technical interviews for healthcare data analyst roles frequently include a live SQL query, a case study on a hospital metric like readmission rates, or a request to interpret a dashboard. Practice narrating your reasoning out loud, not just getting the right answer.
Healthcare Data Analyst Jobs: Frequently Asked Questions
Which companies are hiring the most healthcare data analysts?
The companies hiring the most healthcare data analysts right now include Jobot, VeeRteq Solutions, and EmblemHealth, with the largest share of openings in Texas, Illinois, and New York, based on current listings on Migrate Mate as of November 2026. Health systems, payers, and pharmacy benefit managers consistently represent the largest share of open roles.
How many healthcare data analyst jobs are remote?
About 78% of healthcare data analyst openings are fully remote or hybrid as of November 2026, making it one of the more flexible roles in the healthcare sector. Positions focused on payer analytics, population health reporting, and claims analysis tend to be the most remote-friendly, while roles tied to on-site EHR systems or clinical operations teams are more likely to require in-person work.
How do you become a healthcare data analyst?
Start with a bachelor's degree in health informatics, public health, statistics, or a related field, then build hands-on SQL and data visualization skills through coursework or self-directed projects using publicly available clinical datasets. Certifications in tools like Tableau or platforms like Epic can strengthen your application. Entry-level roles in data coordination or health information management are common stepping stones into a full analyst position.
Can you get a healthcare data analyst job with little or no experience?
Yes, entry-level healthcare data analyst roles exist, and employers filling them often prioritize SQL skills and domain familiarity over years of experience. A portfolio project using a public claims or public health dataset, combined with any coursework or internship in a healthcare setting, can substitute for direct work history. Titles like junior analyst, reporting analyst, or health informatics coordinator are common starting points that lead into analyst roles.
What does the healthcare data analyst interview process look like?
Most healthcare data analyst interview processes include an initial recruiter screen, a technical assessment involving SQL queries or a case study built around a clinical metric like readmission rates or claims denial patterns, and a final panel interview with data team leads or clinical stakeholders. Some employers add a take-home exercise asking you to clean a dataset and present findings, so prepare to walk through your analytical reasoning clearly and concisely.
Where can I find and apply to healthcare data analyst jobs?
You can find and apply to healthcare data analyst jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your skills, experience level, and preferred location, then apply directly to each one that fits.
See All 81 Healthcare Data Analyst Jobs
Find roles that match your experience and apply in just a few clicks.
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