Responsibilities
- Lead the architecture and ongoing development of a cloud-native data platform primarily hosted on Google Cloud Platform, leveraging services such as BigQuery, Cloud Storage, Pub/Sub, Cloud Run, Cloud Composer (Airflow), and Healthcare API.
- Guide strategic choices regarding multi-cloud capabilities, including interoperability with AWS when required.
- Define and promote data engineering best practices, coding standards, and reusable architectural patterns across teams.
- Develop scalable ETL and ELT pipelines using dbt for data transformation and Airflow for workflow orchestration.
- Create robust data ingestion systems for clinical and administrative data in HL7, FHIR, DICOM, and proprietary formats.
- Build and maintain data pipelines tailored for AI and machine learning model development and training.
- Implement both streaming and batch data processing workflows using Pub/Sub, Dataflow, and serverless computing technologies.
- Support or lead integration efforts with AWS-hosted partner systems or data sources when necessary.
- Design and manage BigQuery datasets, semantic models, and data warehouse schemas.
- Apply healthcare data standards such as FHIR to ensure consistent and interoperable data modeling.
- Provide expert guidance on data modeling and data warehousing practices across both Google Cloud and AWS environments.
- Develop and enforce data quality frameworks, including automated testing and real-time monitoring.
- Ensure all data pipelines and cloud infrastructure comply with HIPAA regulations and securely handle PHI and PII.
- Promote data lineage, comprehensive documentation, metadata governance, and adoption of dbt documentation tools.
- Collaborate with analytics, product, clinical informatics, and security teams to deliver reliable and high-quality data products.
- Oversee technical design and implementation of multi-cloud data integrations involving AWS-based systems or partners.
- Support recruitment efforts and contribute to the growth and mentorship of junior data engineers.
Compensation
Competitive salary and equity package
Work Arrangement
Hybrid or remote with team coordination across time zones
Team
Part of a cross-functional data team working closely with clinical, product, and security stakeholders
Responsibilities
- Lead the architecture and ongoing development of a cloud-native data platform primarily hosted on Google Cloud Platform, leveraging services such as BigQuery, Cloud Storage, Pub/Sub, Cloud Run, Cloud Composer (Airflow), and Healthcare API.
- Guide strategic choices regarding multi-cloud capabilities, including interoperability with AWS when required.
- Define and promote data engineering best practices, coding standards, and reusable architectural patterns across teams.
- Develop scalable ETL and ELT pipelines using dbt for data transformation and Airflow for workflow orchestration.
- Create robust data ingestion systems for clinical and administrative data in HL7, FHIR, DICOM, and proprietary formats.
- Build and maintain data pipelines tailored for AI and machine learning model development and training.
- Implement both streaming and batch data processing workflows using Pub/Sub, Dataflow, and serverless computing technologies.
- Support or lead integration efforts with AWS-hosted partner systems or data sources when necessary.
- Design and manage BigQuery datasets, semantic models, and data warehouse schemas.
- Apply healthcare data standards such as FHIR to ensure consistent and interoperable data modeling.
- Provide expert guidance on data modeling and data warehousing practices across both Google Cloud and AWS environments.
- Develop and enforce data quality frameworks, including automated testing and real-time monitoring.
- Ensure all data pipelines and cloud infrastructure comply with HIPAA regulations and securely handle PHI and PII.
- Promote data lineage, comprehensive documentation, metadata governance, and adoption of dbt documentation tools.
- Collaborate with analytics, product, clinical informatics, and security teams to deliver reliable and high-quality data products.
- Oversee technical design and implementation of multi-cloud data integrations involving AWS-based systems or partners.
- Support recruitment efforts and contribute to the growth and mentorship of junior data engineers.
Available for qualified candidates
