Healthcare Data QA Engineer-TI130825

emergiTEL Inc.; Canada; Remote; CAD 85,000 - 120,000; Full time

Job summary

A leading data solutions company is seeking a Healthcare Data QA Engineer to validate and test large-scale data pipelines in the healthcare sector. This role requires deep knowledge in big data technologies like PySpark and Flink, along with expertise in healthcare data standards such as FHIR R4. The ideal candidate will possess strong automation and testing skills, ensuring accuracy and compliance in both real-time and batch processing systems.

Qualifications

• Experience in Backend Data QA focused on Big Data & Healthcare.
• Validate real-time and batch processing systems for data correctness.
• Automate tests and perform regression and performance testing.

Responsibilities

• Write and run test strategies for PySpark/Flink data transformations.
• Validate streaming jobs and batch jobs under different load conditions.
• Ensure compliance with healthcare standards (FHIR R4).

Skills

Big Data & Streaming Testing: PySpark, Flink, Kafka

Healthcare Data Standards: FHIR R4 basics

Python Testing Tools: pytest, unittest

SQL for complex data validation

Familiarity with cloud platforms (AWS/GCP)

Knowledge of QA best practices

Job description

Job Description:

This role is for a Healthcare Data QA Engineer focused on testing large-scale data pipelines that transform diverse healthcare data into FHIR R4–compliant resources using tools like PySpark, Flink, and Kafka.
You’ll validate both real-time (streaming) and batch processing systems, ensuring accuracy, compliance, and clinical relevance of the data. The position blends big data testing, healthcare domain knowledge, and cloud-based QA automation.

Requirements:

1. Type of Role

• Backend Data QA (not UI/web testing)
• Specialization in Big Data & Healthcare
• Focus on data correctness, compliance, and performance

2. Core Responsibilities

• Write and run test strategies for PySpark/Flink data transformations
• Validate streaming jobs and batch jobs under different load conditions
• Ensure FHIR R4 compliance with domain experts
• Automate tests for ingestion, transformation, and output
• Perform regression, schema evolution, and data migration testing
• Conduct performance/load testing for big data pipelines

3. Must-Have Skills

• Big Data & Streaming Testing: PySpark, Flink, Kafka
• Healthcare Data Standards: FHIR R4 basics
• Python Testing Tools: pytest, unittest, Great Expectations, Pandera
• SQL for complex data validation
• Familiarity with cloud platforms (AWS/GCP)
• Knowledge of QA best practices (CI/CD, Git, TDD)

4. Nice-to-Have

• Experience with FHIR/HL7, clinical terminologies (SNOMED, LOINC, ICD)
• PyFlink testing, Flink SQL validation
• Apache Iceberg or other data lake formats
• Knowledge of healthcare compliance (HIPAA, PIPEDA)
• Monitoring/observability tools (Datadog, GCP Monitoring)