Technical Solutions Engineer - Pre

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.

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.

• 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.

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 Big Query, 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…