Data Engineer​/Data Scientist – Healthcare Data Integrations

Position: Data Engineer / Data Scientist – Healthcare Data Integrations
Help Shape the Future of Healthcare Data & AI

This Jobot Job is hosted by:
Robert Donohue
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Salary: $120,000 - $150,000 per year

A bit about us:

We're an AI-powered healthcare technology company helping multi-location healthcare, dental, and veterinary organizations better understand the return on their marketing investments. Our platform connects marketing activity directly to patient appointments, visits, and revenue, giving our customers the insights they need to grow their practices.

As we continue to expand, we're building a dedicated Healthcare Data Integrations team responsible for bringing together data from Electronic Health Records (EHRs) and Practice Management Systems (PMSs). This is an opportunity to join a small, high-impact team where you'll help define processes, build scalable solutions, and play a critical role in the future of our data platform—all while working remotely.

Can we remote for candidates living in any of these states:
North Carolina, Colorado, Florida, Illinois, Indiana, Ohio, Rhode Island, South Carolina, Tennessee, Virginia

Why join us?

• 100% Remote (Must live in any of these states:
  North Carolina, Colorado, Florida, Illinois, Indiana, Ohio, Rhode Island, South Carolina, Tennessee, Virginia)
• Salary: $120,000–$150,000
• Performance Bonus
• Equity (Stock Options)
• 401(k) with 4% company match (immediately vested)
• 100% company-paid employee medical insurance
• 80% company-paid dental insurance
• Company-paid Short-Term & Long-Term Disability
• Vision Insurance
• Unlimited PTO
• Opportunity to build a brand-new Healthcare Data Integrations team
• Work with cutting-edge AI, healthcare, and cloud technologies
• High visibility with significant influence on product and platform direction

Job Details

We're seeking a Data Engineer / Data Scientist who enjoys solving complex data challenges and transforming messy healthcare data into reliable business intelligence.

In this role, you'll evaluate new healthcare data sources, profile data quality, define transformation logic, and partner with engineering to build scalable data ingestion pipelines. Your work will directly impact analytics used to measure patient acquisition, marketing ROI, and revenue across thousands of healthcare providers.

This is a highly collaborative, hands-on role that combines healthcare data, cloud technologies, AI, and data engineering.

Responsibilities
Healthcare Data Analysis

• Evaluate new EHR, PMS, and healthcare partner data sources
• Profile incoming datasets for completeness, consistency, and reporting readiness
• Validate patient, appointment, encounter, and revenue data
• Make data quality recommendations for new integrations

Data Quality & Data Science

• Identify data quality issues impacting reporting accuracy
• Define normalization and mapping logic across multiple healthcare systems
• Build repeatable validation processes
• Ensure high levels of data integrity across all integrations

Data Engineering

• Develop SQL and Python-based validation and transformation processes
• Partner with engineering to build scalable ETL and ingestion pipelines
• Support integrations involving data lakes, cloud storage, Snowflake, and file-based ingestion
• Build monitoring and reconciliation processes to maintain data accuracy

Healthcare Integrations

• Support integrations with EHR and Practice Management Systems
• Work directly with third-party vendors and healthcare technology partners
• Assist with integration onboarding and implementation
• Evaluate build-versus-buy integration strategies

Process Improvement

• Build reusable tooling and templates
• Improve automation around healthcare data validation
• Develop standards and documentation
• Continuously improve integration quality and operational efficiency

Qualifications

• 5–7 years of experience in Data Science, Data Engineering, Analytics Engineering, or Data Quality
• Advanced SQL skills
• Strong Python programming experience
• Experience using Pandas or similar data analysis libraries
• Strong understanding of relational databases and data modeling
• Experience building or supporting ETL and data ingestion pipelines
• Experience working with Snowflake, AWS, S3, data lakes, or cloud…