Hybrid Healthcare Data Solutions Engineer

Verily; Dallas (TX); Hybrid; USD 103,500 - 155,500; Full time

Benefits offered by this job

Bonus

Equity

Benefits

Job summary

Verily Health Inc. is seeking a Data Refinery Technical Solutions Engineer to design and implement cloud-native data pipelines for structured and unstructured healthcare data.

You will work with product, engineering, clinical informatics, and data science teams to onboard data sources including EHRs, registries, genomics, and imaging systems, aligning to FHIR and OMOP models and scaling delivery from discovery to production.

Qualifications

• BA/BS in CS, engineering, biomedical informatics, health informatics, data science or related field.
• 6+ years in healthcare tech, data engineering, or customer-facing technical roles.
• Experience with cloud platforms (GCP, AWS, Azure).
• Proficiency in Python, Golang, Terraform, YAML, and SQL.

Responsibilities

• Analyze customer requirements to design scalable, cloud-native ingestion and transformation pipelines for structured and unstructured data.
• Onboard, integrate, harmonize, and curate healthcare and research data sources (EHRs, registries, genomics, imaging) into FHIR/OMOP models.
• Collaborate with Clinical Informatics to map concepts and support data quality, identity resolution, and longitudinal records.
• Build, configure, and optimize data processing workflows; provide enablement, training, and support from discovery to production deployment.
• Partner with product/engineering/sales to influence direction and develop reusable technical assets.

Skills

Python

Golang

Terraform

YAML

SQL

Cloud platforms

Education

BA/BS or equivalent

Tools

Google Cloud Platform (GCP)

Amazon Web Services (AWS)

Microsoft Azure

Terraform

SQL

Job description

Verily Health Inc. is seeking a Data Refinery Technical Solutions Engineer to design and implement cloud-native data pipelines for structured and unstructured healthcare data.

You will work with product, engineering, clinical informatics, and data science teams to onboard data sources including EHRs, registries, genomics, and imaging systems, aligning to FHIR and OMOP models and scaling delivery from discovery to production.