John Snow Labs is an award-winning AI and NLP company, accelerating progress in data science by providing state-of-the-art software, data, and models. Founded in 2015, it helps healthcare and life science companies build, deploy, and operate AI products and services. John Snow Labs is the winner of the 2018 AI Solution Provider of the Year Award, the 2019 AI Platform of the Year Award, the 2019 International Data Science Foundation Technology award, and the 2020 AI Excellence Award.

John Snow Labs is the developer of Spark NLP - the world’s most widely used NLP library in the enterprise - and is the world’s leading provider of state-of-the-art clinical NLP software, powering some of the world’s largest healthcare & pharma companies. John Snow Labs is a global team of specialists, of which 33% hold a Ph.D. or M.D. and 75% hold at least a Master’s degree in disciplines covering data science, medicine, software engineering, pharmacy, DevOps and SecOps.

We are seeking a Healthcare Data Integration Engineer to lead clinical data integration efforts.

This role will be responsible for connecting client systems to our platform, designing and implementing data ingestion pipelines, and ensuring that healthcare data is transformed into standardized models suitable for analytics and AI applications.

The ideal candidate combines healthcare interoperability expertise with strong technical implementation skills. You should be comfortable working directly with client technical teams, understanding source systems, designing mappings, and building robust integration solutions.

Responsibilities

Client Onboarding & Integration

* Lead technical onboarding activities for new clients.
* Analyze source systems and data architectures.
* Design and implement connectors to various data sources, including:

 * EHR systems
 * FHIR servers
 * HL7 interfaces
 * Relational databases
 * Data warehouses
 * Cloud storage platforms (S3, Azure Blob, GCS)
 * Flat-file and CSV-based exchanges
 * APIs and custom integrations
* Collaborate with client IT and clinical informatics teams to understand source data structures and workflows.
* Define integration strategies and technical specifications.

Healthcare Data Standardization

* Map source data into healthcare interoperability standards and common data models.
* Support transformation of clinical data into OMOP CDM.
* Develop and maintain source-to-target mappings.
* Identify and resolve data quality, terminology, and interoperability issues.
* Participate in vocabulary mapping activities involving:

 * SNOMED CT
 * ICD-10
 * LOINC
 * RxNorm
 * CPT
 * Other local and proprietary terminologies

Data Engineering

* Build, test, and maintain ETL/ELT pipelines.
* Develop reusable integration frameworks and connector libraries.
* Monitor integration processes and troubleshoot production issues.
* Improve automation of onboarding and data validation workflows.
* Document integration designs, mappings, and operational procedures.

Collaboration

* Work closely with data engineers, data scientists, and machine learning engineers.
* Support data validation and quality assurance activities.
* Contribute to interoperability best practices and platform architecture.
* Serve as a technical point of contact during onboarding projects.

Required Qualifications

* 2+ years of experience in healthcare data integration, interoperability, or clinical data engineering.
* Experience working with healthcare data standards, including:

 * FHIR
 * HL7 v2
 * Clinical terminology systems
* Experience with SQL and relational databases.
* Experience designing and implementing ETL pipelines.
* Experience consuming and integrating REST APIs.
* Understanding of healthcare data domains such as:

 * Encounters
 * Conditions
 * Procedures
 * Medications
 * Measurements/Laboratory results
 * Clinical observations
* Strong problem-solving and troubleshooting skills.
* Excellent communication skills and ability to work directly with client technical teams.

Preferred Qualifications

* Experience with OMOP CDM.
* Experience with OHDSI tools and ecosystem.
* Experience mapping source systems to OMOP standard vocabularies.
* Experience with terminology services and vocabulary management.
* Familiarity with Epic, Cerner, MEDITECH, Athenahealth, eClinicalWorks, or other EHR platforms.
* Experience with healthcare cloud environments.
* Experience with Python and modern data engineering tools.
* Experience with healthcare analytics or research platforms.

Nice to Have

* Experience implementing FHIR servers or FHIR APIs.
* Experience with healthcare NLP or unstructured clinical data.
* Experience with data quality frameworks.
* Experience supporting regulatory or research data initiatives.
* Familiarity with observational research and real-world evidence platforms.

What Success Looks Like

Within your first year, you will:

* Lead onboarding and integration projects for new clients.
* Build reusable connectors that reduce onboarding effort.
* Help standardize diverse healthcare data sources into OMOP CDM.
* Improve terminology mapping and data quality processes.
* Become a trusted technical partner for client integration efforts.
* Contribute to the evolution of a modern healthcare data and AI platform.

Our Commitment to You  

At John Snow Labs, we believe that diversity is the catalyst of innovation. We’re committed to empowering talented people from every background and perspective to thrive.   

 We are an award-winning global collaborative team focused on helping our customers put artificial intelligence to good use faster. Our website includes The Story of John Snow, and our Social Impact page details how purpose and giving back is part of our DNA. More at JohnSnowLabs.com 

• We are a fully virtual company, collaborating across 28 countries.
• This is a contract opportunity, not a full-time employment role.
• This role requires the availability of at least 30-40 hours per week.

Location

Remote-friendly. Preference for candidates able to collaborate during North American business hours.

Compensation

Competitive salary based on experience and location.