Mid Level Healthcare Data Analyst Jobs
Mid level healthcare data analyst jobs go to analysts ready to own data pipelines and reporting workflows end to end, collaborate across clinical and operational teams, and translate findings into decisions with minimal oversight. Roles are concentrated in Staffing & Recruiting, Technology & Software, and Distribution & Wholesale, with a mix of on-site, hybrid, and remote positions, and employers like Jobot, Amazon Web Services, and MERCOR hiring at this level now.
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INTRODUCTION
Incredible opportunity to join a fast growing AI-driven healthcare technology company!
ABOUT THE ROLE
This Jobot Job is hosted by: Craig Rosecrans
Are you a fit? Easy Apply now by clicking the "Easy Apply" button and sending us your resume.
COMPENSATION
- Salary: $120,000 - $150,000 per year
A BIT ABOUT US
Our client is an award-winning, AI-driven healthcare technology company that's transforming how multi-location healthcare organizations leverage data to make smarter business decisions. As they continue to scale, they're building a brand-new Healthcare Data Integrations team responsible for ensuring the quality, integrity, and reliability of the data powering their analytics platform. This is an opportunity to join a small, highly collaborative team where you'll have significant ownership and influence over the tools, standards, and processes that support the company's next phase of growth.
WHY JOIN US?
- Competitive Base Salary
- Company paid health plan for employees
- Equity in high-growth start-up (not in lieu of a salary)
- Flexible Hours
- Very generous PTO
- Dental and Vision, FSA, HSA
- Small team, autonomy
- Many more great perks!
JOB DETAILS
As a Senior Healthcare Data Engineer, you'll work at the intersection of healthcare data, engineering, and analytics. You'll evaluate new data sources, design scalable data transformations, and ensure complex healthcare datasets are accurate enough to support critical business reporting. You'll partner closely with software engineers, product leaders, and external integration partners to solve challenging data quality problems while helping build a scalable framework for future healthcare integrations.
Responsibilities
- Profile and validate data from Electronic Health Record (EHR) and Practice Management (PMS) systems.
- Analyze complex healthcare datasets to determine completeness, consistency, and reporting readiness.
- Design data mapping and normalization logic across disparate source systems.
- Partner with engineering to build and enhance production ETL and data ingestion pipelines.
- Develop automated monitoring, reconciliation, and data quality validation processes.
- Collaborate with external vendors and integration partners to resolve data issues.
- Help establish best practices, reusable tooling, and scalable processes for future integrations.
BASIC QUALIFICATIONS
- 5+ years of experience in Data Engineering, Analytics Engineering, Data Science, or Data Quality Engineering.
- Expert-level SQL skills.
- Strong Python experience, including pandas or similar data processing libraries.
- Experience building or supporting ETL pipelines and data ingestion workflows.
- Strong understanding of relational databases, data modeling, and schema design.
- Ability to investigate complex data quality issues and communicate technical findings clearly.
- Experience working with cloud data platforms such as Snowflake, AWS, S3, or similar technologies.
PREFERRED QUALIFICATIONS
- Healthcare data experience involving EHR, EMR, Practice Management Systems, clinical, financial, or claims data.
- Knowledge of FHIR or healthcare interoperability standards.
- Experience working with HIPAA-protected data.
- Familiarity with healthcare integration platforms or third-party data aggregators.
Interested in hearing more? Easy Apply now by clicking the "Easy Apply" button.
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Who's Hiring



Top Industries Hiring
- Staffing & Recruiting
- Technology & Software
- Distribution & Wholesale
- Insurance
- Healthcare & Medical Services
Mid Level Healthcare Data Analyst Jobs: Frequently Asked Questions
How do I get a mid level healthcare data analyst job?
Position your experience around ownership, not just contribution. Highlight projects where you drove the analysis from data pull to stakeholder presentation, tools you used independently, and any cross-functional work with clinical, finance, or operations teams. Applications that show measurable impact, such as reduced reporting time or improved data quality, stand out over those that list responsibilities without outcomes.
Which companies hire mid level healthcare data analysts?
Companies hiring mid level healthcare data analysts right now include Jobot, Amazon Web Services, and MERCOR, based on current listings on Migrate Mate as of August 2026. Hiring at this level covers health systems, payers, pharmacy benefit managers, and health technology vendors, all of which need analysts who can work independently on ongoing reporting and ad hoc requests.
Are there remote mid level healthcare data analyst jobs?
Yes, remote and hybrid options are common at this experience level. About 45% of mid level healthcare data analyst openings are remote or hybrid as of August 2026, reflecting how much of this work centers on querying databases, building dashboards, and presenting findings in virtual settings rather than requiring on-site presence.
How do I move up to a mid level healthcare data analyst role?
The path from entry level to mid level is built on deepening technical skills, such as moving from assisted SQL queries to independently structuring complex ones, and taking ownership of full projects rather than single tasks. Analysts who demonstrate consistent delivery, ask for stretch assignments, and quantify the impact of their work, such as accuracy improvements or process efficiencies, typically make that jump within a few years.
Which industries hire the most mid level healthcare data analysts?
Mid Level healthcare data analyst roles concentrate in Staffing & Recruiting, Technology & Software, and Distribution & Wholesale, based on current listings on Migrate Mate as of August 2026. These sectors generate high volumes of claims, clinical, and operational data that require experienced analysts who can work with complex datasets without heavy oversight and communicate findings to both technical and non-technical stakeholders.