Guidehouse is looking to support future opportunities by building, scaling, and maintaining national-scale data pipelines, integrations, and storage solutions that power laboratory, research, and healthcare operations.
Requirements
- Deep, practical knowledge of healthcare data, common data models (OMOP, FHIR), and clinical terminologies (such as ICD, SNOMED, RxNorm).
- Solid experience with big data technologies (Apache Spark, Hadoop), containerization (Docker), and reproducible/scalable workflows.
- Hands-on experience with cloud services and REST API integrations.
- Strong SQL, Python, and version control (Git) skills.
- Experience with privacy-preserving record linkage (PPRL), federated data systems, and regulated environments (FISMA, HIPAA).
- Designing/deploying data solutions on cloud platforms (AWS, GCP, Azure).
- Proficiency with workflow management systems (Nextflow, Snakemake, Airflow).
Responsibilities
- Architect and modernize robust, disease-agnostic data acquisition and ingestion pipelines for large-scale, heterogeneous healthcare data (e.g., EHRs, claims, registries, geospatial data).
- Design, implement, and maintain ETL/ELT pipelines across cloud platforms (AWS, Azure, GCP).
- Design and maintain scalable, reliable, and flexible applications using TypeScript, NodeJS, Angular, and RESTful web services to support data workflows.
- Integrate data sources including ELN, LIMS, sample tracking software, web-based portals, and REST APIs.
- Maintain and enhance data harmonization pipelines such as OMOP, improve interoperability among data models including OMOP, PCORNet, and FHIR, and ensure consistency and alignment for critical data types to support master data integration and harmonization.
- Implement and manage data storage solutions (data lakes, warehouses) utilizing the appropriate partitioning, security, and lifecycle policies.
- Champion data quality and governance standards through the development of sophisticated data quality frameworks, dashboards, and feedback loops to ensure transparency in data completeness, consistency, and quality for partners and researchers.
Other
- Bachelor’s degree in Computer Science, Engineering, Data Engineering, Bioinformatics, or related field.
- A minimum of EIGHT (8) years of hands-on data engineering experience
- Ability to Obtain Public Trust
- Travel Required: None
- Master’s degree is preferred
