Qualified Health PBC - Healthcare AI Solutions Engineer
Requirements
• 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: • Strong analytical toolkit • PySpark for distributed data processing • PySpark • Advanced SQL for data querying and transformation • Advanced SQL • Excel for data analysis and reporting • Excel • 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 • Data quality focus • Healthcare data experience: Prior work with healthcare datasets (EHR, claims, clinical, lab data) • Consultant mindset: ability to earn trust quickly, communicate complex ideas to diverse audiences, and deliver value in client-facing environments • Consultant mindset • Ownership Mentality: takes full accountability for the quality and outcome of your work from scoping through production • Ownership Mentality: • Attention to detail: Commitment to accuracy, testing, and delivering reliable solutions • Attention to detail • Collaborative working style: Comfortable partnering with non-technical colleagues and adapting to feedback • Collaborative working style • Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or related technical field • Bachelor's degree • 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 • Healthcare data standards knowledge • Azure cloud platform: Hands-on experience with Azure Databricks, Data Factory, Blob Storage, Delta Lake • Azure cloud platform • Healthcare compliance awareness: Understanding of HIPAA requirements and healthcare data security best practices • Healthcare compliance awareness • 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 • DevOps practices • Performance tuning: Proven ability to optimize complex data transformations for scale • Performance tuning • 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 • Multiple data format fluency: • Experience with AI-assisted development tools (e.g., GitHub Copilot, Cursor, or similar) to accelerate coding and prototyping • Experience with AI-assisted development tools • Prior experience in a client-facing technical consulting, forward deployment, or solutions engineering role • Prior experience in a client-facing technical consulting • Technical Environment: • Our data infrastructure is built on modern cloud technologies including: • Azure Databricks + Data Factory (plus Fabric and Snowflake integrations) • Azure Databricks + Data Factory • PySpark • GitHub Actions + Terraform for CI/CD and Infrastructure as Code • GitHub Actions + Terraform • Python with type-safe patterns and modern frameworks • Python • AI-assisted development tooling for accelerated engineering • AI-assisted development tooling • 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 • High-quality data pipelines • Proactive issue identification with technical problems caught and resolved before impacting partners • Proactive issue identification • Reusable components that reduce implementation time for subsequent integrations • Reusable components • Clean production deployments with minimal post-launch issues • Clean production deployments • Technical credibility with partner IT teams based on quality of work • Technical credibility • Efficient troubleshooting with quick diagnosis and resolution of data quality issues • Efficient troubleshooting • Impact & Growth Opportunity: • As a Healthcare AI Solutions 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.
Responsibilities
• Technical Implementation & Development • Design and build ETL pipelines using PySpark, SQL, and Azure data services to process healthcare data from multiple source systems • Design and build ETL pipelines • Execute data extraction and transformation operations on complex healthcare datasets, ensuring accuracy and compliance with established standards • Execute data extraction and transformation • Develop data quality validation frameworks to identify and resolve issues during integration, QC, and backtesting phases • Develop data quality validation • Troubleshoot technical issues including data schema mismatches, transformation logic errors, and performance bottlenecks -- independently diagnosing root causes and driving resolution • Troubleshoot technical issues • Build reusable data components and standardized integration patterns that accelerate future implementations • Build reusable data components • Optimize pipeline performance for large-scale healthcare datasets, ensuring efficient processing and resource utilization • Optimize pipeline performance • Implement data validation rules specific to healthcare contexts (e.g., clinical code validation, temporal logic checks, referential integrity) • Implement data validation rules • Write and maintain technical documentation for data pipelines, transformations, and integration patterns • Write and maintain technical documentation • Support production deployments by coordinating with infrastructure teams and conducting final testing • Support production deployments • Leverage AI-assisted code development tools to accelerate delivery and improve solution quality • Leverage AI-assisted code • Client Consulting & Collaboration • Serve as a trusted technical advisor to health system partners, translating complex data and AI concepts into clear, actionable guidance • Serve as a trusted technical advisor • Partner with Data Integration Manager to translate partner requirements into precise technical specifications • Partner with Data Integration Manager • Participate in technical discussions with partner IT teams to understand data schemas, access methods, and integration constraints • Participate in technical discussions • Provide expert guidance on data mapping specifications, transformation approaches and architecture decisions • Provide expert guidance • Identify data quality issues and work with Manager to coordinate resolution with partners • Identify data quality issues • Communicate technical findings from QC and backtesting clearly to both technical and non-technical stakeholders • Communicate technical findings • Adapt consulting approach and communication style to the culture and maturity of each partner enviornment • Adapt consulting approach and communication style • Contribute to continuous improvement of tools, processes, and technical standards • Contribute to continuous improvement • Product Prototyping & Innovation • Support rapid prototyping of new AI-powered product features and data capabilities in close collaboration with product and engineering teams • Support rapid prototyping • Translate partner use cases and field insights into prototype solutions that demonstrate the potential of the Qualified Health platform • Translate partner use cases and field insights • Build and iterate on proof-of-concept integrations and analytical tools to test new approaches before full-scale implementation • Build and iterate on proof-of-concept integrations • Leverage AI-assisted development practices to compress prototyping cycles and explore solutions at speed • Leverage AI-assisted development practices • Document learnings and outcomes from prototyping efforts to inform product roadmap decisions and reusable patterns • Document learnings and outcomes • Bring a builder’s mindset to ambiguous problem spaces, moving quickly from idea to working demonstration • Bring a builder’s mindset to ambiguous problem spaces
Benefits
• 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
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