Data Integration Engineer - Healthcare Data Infrastructure

Job Description

Job Description

Transform healthcare with us.

Qualified Health is seeking a Data Integration Engineer to serve as the technical implementation specialist for our healthcare data integration initiatives. In this hands-on role, you'll design and build robust data pipelines that transform raw healthcare data from diverse sources (Epic, LIMS, PACS, SharePoint, etc.) into production-ready datasets powering our AI platform. You'll work in close partnership with a Data Integration Manager who handles client relationships and program coordination, allowing you to focus on solving complex technical challenges, ensuring data quality, and building reusable integration patterns. Your roles are complementary:

You own: Technical implementation, ETL development, data quality validation, pipeline construction, troubleshooting, and production deployment execution

Manager owns: Partner relationships, requirements gathering, timeline management, stakeholder communication, issue escalation, and ensuring delivery meets expectations

Together you deliver: Successful data integrations that meet partner needs on time with high quality

This is a technical role for someone who loves working with data, enjoys solving puzzles, and takes pride in building reliable, production-grade solutions.

Key Responsibilities:

Technical Implementation & Development (80%)

• Design and build ETL pipelines using PySpark, SQL, and Azure data services to process healthcare data from multiple source systems
• Execute data extraction and transformation operations on complex healthcare datasets, ensuring accuracy and compliance with established standards
• Develop data quality validation frameworks to identify and resolve issues during integration, QC, and backtesting phases
• Troubleshoot technical issues including data schema mismatches, transformation logic errors, and performance bottlenecks
• Build reusable data components and standardized integration patterns that accelerate future implementations
• Optimize pipeline performance for large-scale healthcare datasets, ensuring efficient processing and resource utilization
• Implement data validation rules specific to healthcare contexts (e.g., clinical code validation, temporal logic checks, referential integrity)
• Write and maintain technical documentation for data pipelines, transformations, and integration patterns
• Support production deployments by coordinating with infrastructure teams and conducting final testing

Collaboration & Problem-Solving (20%)

• Partner with Data Integration Manager to translate partner requirements into technical specifications
• Participate in technical discussions with partner IT teams to understand data schemas, access methods, and integration constraints
• Provide technical guidance on data mapping specifications and transformation approaches
• Identify data quality issues and work with Manager to coordinate resolution with partners
• Share technical findings from QC and backtesting with Manager to inform partner conversations
• Contribute to continuous improvement of tools, processes, and technical standards

Required Qualifications:

• 5+ years of experience in data analytics, data engineering, or solution delivery roles, with demonstrated expertise in data integration and ETL processes
• Strong analytical toolkit with proficiency in:
  • PySpark for distributed data processing
  • Advanced SQL for data querying and transformation
  • Excel for data analysis and reporting
• Production ETL experience: Track record of building and maintaining production-grade data pipelines with proper error handling and monitoring
• Data quality focus: Experience implementing validation frameworks and troubleshooting data quality issues
• Healthcare data experience: Prior work with healthcare datasets (EHR, claims, clinical, lab data)
• Problem-solving mindset: Ability to independently diagnose and resolve complex technical issues
• Attention to detail: Commitment to accuracy, testing, and delivering reliable solutions
• Collaborative working style: Comfortable partnering with non-technical colleagues and adapting to feedback
• Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or related technical field

Preferred Skills:

• Epic Clarity experience: Direct work with Epic's relational database structure and clinical data models
• Healthcare data standards knowledge: Understanding of FHIR, HL7v2, DICOM, LOINC, SNOMED, ICD-10
• Azure cloud platform: Hands-on experience with Azure Databricks, Data Factory, Blob Storage, Delta Lake
• Healthcare compliance awareness: Understanding of HIPAA requirements and healthcare data security best practices
• Data warehouse/lakehouse experience: Familiarity with dimensional modeling and modern data architecture patterns
• DevOps practices: Experience with Git, CI/CD pipelines, and infrastructure-as-code
• Performance tuning: Proven ability to optimize complex data transformations for scale
• LIMS/PACS experience: Prior work integrating laboratory or imaging systems data
• Multiple data format fluency: Experience with JSON, XML, Parquet, CSV, and other healthcare interchange formats

Technical Environment:

Our data infrastructure is built on modern cloud technologies including:

• Azure Databricks + Data Factory (plus Fabric and Snowflake integrations)
• PySpark for distributed data processing
• GitHub Actions + Terraform for CI/CD and Infrastructure as Code
• Python with type-safe patterns and modern frameworks
• Healthcare data formats including FHIR, Epic Clarity, and other EHR schemas

What Success Looks Like:

• High-quality data pipelines delivered on schedule with thorough testing and documentation
• Proactive issue identification with technical problems caught and resolved before impacting partners
• Reusable components that reduce implementation time for subsequent integrations
• Clean production deployments with minimal post-launch issues
• Technical credibility with partner IT teams based on quality of work
• Efficient troubleshooting with quick diagnosis and resolution of data quality issues

Impact & Growth Opportunity:

As a Data Integration Engineer at Qualified Health, you'll build the data infrastructure that powers AI-driven insights for major health systems. Your work directly enables better patient care by ensuring high-quality, reliable data flows into clinical decision support tools. This role offers deep technical learning in healthcare data, exposure to diverse health system architectures, and growth potential into senior technical or platform architecture roles as we scale.

Why Join Qualified Health?

This is an opportunity to join a fast-growing company and a world-class team, that is poised to change the healthcare industry. We are a passionate, mission-driven team that is building a category-defining product. We are backed by premier investors and are looking for founding team members who are excited to do the best work of their careers.

Our employees are integral to achieving our goals so we are proud to offer competitive salaries with equity packages, robust medical/dental/vision insurance, flexible working hours, hybrid work options and an inclusive environment that fosters creativity and innovation.

Our Commitment to Diversity

Qualified Health is an equal opportunity employer. We believe that a diverse and inclusive workplace is essential to our success, and we are committed to building a team that reflects the world we live in. We encourage applications from all qualified individuals, regardless of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, marital status, disability, or veteran status.

Pay & Benefits: The pay range for this role is between $130,000 and $180,000, and will depend on your skills, qualifications, experience, and location. This role is also eligible for equity and benefits.

Join our mission to revolutionize healthcare with AI. To apply, please send your resume through the application below.