Posted 2 days ago
Data Engineer - Clinical Data Experience
@ Kaizen Technologies
Toronto, Ontario
Overview
Kaizen Technologies is hiring a contract Python and PySpark developer in Toronto to build clinical document pipelines. The work centres on parsing CCD/C-CDA clinical XML into structured data across multiple EHR vendors.
Responsibilities:
- Build Python CCD/C-CDA parsing and clinical processing solutions
- Extract demographics, medications, labs and other clinical data from XML
- Develop scalable Python and PySpark data pipelines
- Onboard new vendors into a reusable framework
- Troubleshoot data-quality issues and production incidents
Requirements summary:
- Strong hands-on Python and PySpark experience
- Practical CCD/C-CDA XML parsing experience
- Strong SQL and relational database experience
- Knowledge of clinical terminologies such as LOINC, SNOMED CT and ICD-10
- Experience with multiple EHR vendor implementations
Tools & skills
Source and dates
Source type not verified · apify-linkedin
- Employer posting date
- 2026-11-13
- First seen by our source
- 2026-11-15
- Source record updated
- 2026-11-15
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Software development |
| Experience | 15+ years |
| Travel | air: none · ground: none |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Kaizen Technologies
| Field | Value |
|---|---|
| Open jobs on Jobsy | 1 |
Job Title : Data Engineer - Clinical Data Experience
Location: TORONTO, Canada
Skill Cluster : DE-Python_Full Stack (with SQL), Frameworks, DevOps.
Primary Skill : Python
Experience : 15 years
Job Description :
- We are looking for a hands-on Python / PySpark Developer with practical experience processing CCD/C-CDA clinical documents and building scalable healthcare data pipelines
Key Responsibilities
- Develop and enhance Python-based CCD/C-CDA parsing and clinical data processing solutions.
- Analyze raw CCD/C-CDA XML and extract clinical information such as demographics, encounters, diagnoses, medications, allergies, immunizations, vitals, labs, and procedures.
- Build reusable and scalable parsing logic that can support multiple EHRs, HIEs, vendors, and CCD variations.
- Onboard new CCD vendors into an existing framework with minimal vendor-specific code.
- Develop scalable data processing pipelines using Python and PySpark.
- Handle large numbers of files and large XML documents efficiently.
- Implement validation, error handling, logging, reconciliation, retry, and source-lineage capabilities.
- Troubleshoot missing, duplicate, malformed, or incorrectly interpreted clinical data.
- Optimize processing performance and support production incidents and root-cause analysis.
- Develop automated unit and regression tests to ensure new vendor changes do not impact existing integrations.
- Work with upstream providers and internal teams to resolve data-quality and clinical mapping issues.
Required Skills
- Strong hands-on Python development.
- Strong PySpark and large-scale data processing experience.
- Practical experience with XML parsing and CCD/C-CDA documents.
- Experience developing or significantly enhancing CCD/C-CDA parsers.
- Good understanding of clinical data domains such as Labs, Vitals, Problems, Medications, Immunizations, Allergies, Procedures, and Encounters.
- Experience handling different vendor/EHR implementations of CCD/C-CDA.
- Strong SQL and relational database experience.
- Experience with clinical terminology such as LOINC, SNOMED CT, ICD-10, CPT/HCPCS, RxNorm, and CVX.
- Experience designing modular, reusable, and configuration-driven solutions rather than vendor-specific hardcoded parsers.
Preferred Skills
- AWS experience including S3, Lambda, Glue, ECS/Fargate, Step Functions, SQS/SNS, CloudWatch, or similar services.
- Experience with Epic, Cerner, Meditech, HIEs, or other EHR/clinical data sources.
- Healthcare payer, population health, or clinical quality reporting experience.
- HEDIS / NCQA knowledge is an advantage but not mandatory
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