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Forward Deployed Engineer

Qualified Health · United States · 1 mo ago
RemoteRemoteEngineeringFull-time

Job Summary

Qualified Health is seeking a Forward Deployed Engineer to serve as a technical implementation specialist and forward-deployed consultant for our healthcare data integration and AI initiatives.

Key Responsibilities

  • 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 – independently diagnosing root causes and driving resolution.

  • 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.

  • Leverage AI-assisted code development tools to accelerate delivery and improve solution quality.

Client Consulting & Collaboration

  • Serve as a trusted technical advisor to health system partners, translating complex data and AI concepts into clear, actionable guidance.

  • Partner with Data Integration Manager to translate partner requirements into precise technical specifications.

  • Participate in technical discussions with partner IT teams to understand data schemas, access methods, and integration constraints.

  • Provide expert guidance on data mapping specifications, transformation approaches, and architecture decisions.

  • Identify data quality issues and work with Manager to coordinate resolution with partners.

  • Communicate technical findings from QC and backtesting clearly to both technical and non-technical stakeholders.

  • Adapt consulting approach and communication style to the culture and maturity of each partner environment.

  • Contribute to continuous improvement of tools, processes, and technical standards.

Product Prototyping & Innovation

  • Support rapid prototyping of new AI-powered product features and data capabilities in close collaboration with product and engineering teams.

  • Translate partner use cases and field insights into prototype solutions that demonstrate the potential of the Qualified Health platform.

  • Build and iterate on proof-of-concept integrations and analytical tools to test new approaches before full-scale implementation.

  • Leverage AI-assisted development practices to compress prototyping cycles and explore solutions at speed.

  • Document learnings and outcomes from prototyping efforts to inform product roadmap decisions and reusable patterns.

  • Bring a builder’s mindset to ambiguous problem spaces, moving quickly from idea to working demonstration.

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, Data quality focus, Experience implementing validation frameworks and troubleshooting data quality issues, Azure cloud platform: Hands-on experience with Azure Databricks, Data Factory, Blob Storage, Delta Lake, Consultant mindset: ability to earn trust quickly, communicate complex ideas to diverse audiences, and deliver value in client-facing environments, Ownership Mentality: takes full accountability for the quality and outcome of your work from scoping through production, 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 experience: Prior work with healthcare datasets (EHR, claims, clinical, lab data).

  • Healthcare data standards knowledge: Understanding of FHIR, HL7v2, DICOM, LOINC, SNOMED, ICD-10.

  • 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.

  • Experience with AI-assisted development tools (e.g., GitHub Copilot, Cursor, or similar) to accelerate coding and prototyping.

  • Prior experience in a client-facing technical consulting, forward deployment, or solutions engineering role.

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