Values

The ad says“Experience with unstructured data processing techniques, NLP, AI/ML workflows, or biomedical data abstraction.”
The ad says“Experience working with healthcare or life sciences data, including EHR systems such as Epic, Cerner, Allscripts, or other clinical systems.”
The ad says“Experience building APIs and integrating systems using modern interoperability standards.”
The ad says“Familiarity with data warehousing and analytics technologies such as BigQuery, Snowflake, Databricks, or Spark.”
The ad says“Familiarity with healthcare and research data standards, including FHIR, HL7, CCD/C-CDA, ICD, SNOMED, LOINC, and other healthcare terminology systems.”
The ad says“Experience working with healthcare or life sciences data, including EHR systems such as Epic, Cerner, Allscripts, or other clinical systems.”
The ad says“Familiarity with data warehousing and analytics technologies such as BigQuery, Snowflake, Databricks, or Spark.”
The ad says“Experience working with healthcare or life sciences data, including EHR systems such as Epic, Cerner, Allscripts, or other clinical systems.”
The ad says“Experience designing, implementing, and debugging ETL/ELT pipelines and managing large-scale datasets.”
The ad says“Familiarity with healthcare and research data standards, including FHIR, HL7, CCD/C-CDA, ICD, SNOMED, LOINC, and other healthcare terminology systems.”
The ad says“Familiarity with healthcare and research data standards, including FHIR, HL7, CCD/C-CDA, ICD, SNOMED, LOINC, and other healthcare terminology systems.”
The ad says“Familiarity with healthcare and research data standards, including FHIR, HL7, CCD/C-CDA, ICD, SNOMED, LOINC, and other healthcare terminology systems.”
The ad says“Familiarity with healthcare and research data standards, including FHIR, HL7, CCD/C-CDA, ICD, SNOMED, LOINC, and other healthcare terminology systems.”
The ad says“Experience with unstructured data processing techniques, NLP, AI/ML workflows, or biomedical data abstraction.”
The ad says“Familiarity with healthcare and research data standards, including FHIR, HL7, CCD/C-CDA, ICD, SNOMED, LOINC, and other healthcare terminology systems.”
The ad says“Familiarity with data warehousing and analytics technologies such as BigQuery, Snowflake, Databricks, or Spark.”
The ad says“Familiarity with data warehousing and analytics technologies such as BigQuery, Snowflake, Databricks, or Spark.”

Who We Are

Verily Health is a data platform and technology company purpose-built to power AI-enabled precision health solutions that accelerate research and improve care for individuals and communities. Uniquely positioned at the intersection of technology, data science, and healthcare, Verily transforms multimodal health data into insights, models, and actions that make healthcare more personalized, predictive, and precise.

Description

The Verily Data Refinery team partners with healthcare organizations, life sciences companies, research institutions, and data stewards to transform fragmented healthcare and research data into scalable, curated, and analysis-ready datasets. We work at the intersection of clinical data, cloud technology, and data science to enable customers to ingest, harmonize, enrich, and operationalize structured and unstructured data across complex ecosystems.

As a Data Refinery Technical Solutions Engineer, you will serve as a trusted technical advisor and implementation partner, helping customers build data pipelines and curation strategies that unlock meaningful insights and accelerate biomedical research and healthcare innovation. You will work closely with Product, Engineering, Clinical Informatics, Data Science, and Commercial teams to shape both customer solutions and future product capabilities.

Responsibilities

Analyze customer technical and business requirements to design implementation architectures, data strategies, and scalable cloud-native ingestion and transformation pipelines for structured and unstructured data.
Partner directly with customers to onboard, integrate, harmonize, and curate healthcare and research data sources including EHRs, registries, genomic and imaging systems, and custom datasets into standardized models such as FHIR and OMOP.
Collaborate with Clinical Informatics teams to map and normalize clinical concepts, terminology systems, and workflows, while supporting patient identity resolution, longitudinal record generation, data linking, and data quality validation.
Build, configure, and optimize data processing workflows, while providing technical enablement, training, best practices, and implementation support from discovery and proof of concept through pilot and production deployment.
Partner with Product, Engineering, and Sales teams to influence product direction through customer feedback and develop reusable technical assets, reference architectures, implementation playbooks, and automation frameworks that improve delivery scalability.

Qualifications

Minimum Qualifications

BA/BS degree in Computer Science, Engineering, Biomedical Informatics, Health Informatics, Data Science, or a related field, or equivalent practical experience.
6+ years of experience in healthcare technology, data engineering, technical consulting, solutions engineering, or similar customer-facing technical roles.
Hands-on experience with cloud platforms such as Google Cloud Platform (GCP), Amazon Web Services (AWS), and/or Microsoft Azure.
Proficiency in Python, Golang, Terraform, YAML, and SQL, including the ability to develop solutions and optimize moderately complex queries.
Strong analytical, problem-solving, communication, and project management skills, with a demonstrated ability to take ownership, proactively solve customer challenges, and manage multiple engagements simultaneously.

Preferred Qualifications

Experience working with healthcare or life sciences data, including EHR systems such as Epic, Cerner, Allscripts, or other clinical systems.
Experience designing, implementing, and debugging ETL/ELT pipelines and managing large-scale datasets.
Familiarity with healthcare and research data standards, including FHIR, HL7, CCD/C-CDA, ICD, SNOMED, LOINC, and other healthcare terminology systems.
Familiarity with data warehousing and analytics technologies such as BigQuery, Snowflake, Databricks, or Spark.
Understanding of clinical data harmonization, patient matching, longitudinal record generation, and data quality frameworks.
Experience with unstructured data processing techniques, NLP, AI/ML workflows, or biomedical data abstraction.
Experience building APIs and integrating systems using modern interoperability standards.

Qualified applicants must not require employer sponsored work authorization now or in the future for employment in the United States.

Compensation Information

The US base salary range for this full-time position is $103,500 - $155,500 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.

Verily Health Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here.

If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.