Senior Data Engineer
Tasks
- Architect and provision cloud data infrastructure on GCP
- Build and optimize data models in cloud data warehouses
- Build data observability dashboards and alerting
- Collaborate with data scientists on datasets and feature stores
- Design ELT/ETL pipelines
- Design data lake and lakehouse patterns
- Develop streaming and real time data pipelines
- Drive adoption of CI CD practices for data pipelines
- Ensure HIPAA and privacy compliance
- Establish testing standards for data pipelines
- Implement data masking deidentification and audit logging
- Implement data quality frameworks and validation rules
- Implement orchestration and monitoring for data workflows
- Integrate and normalize clinical datasets using healthcare interoperability standards
- Maintain data governance and data lineage
- Mentor junior data engineers
- Optimize cloud resources for cost efficiency and reliability
Perks/Benefits
Skills/Tech-stack
AWS Kinesis | Access Controls | Apache Airflow | Apache Kafka | Audit Logging | BigQuery | CI/CD | Cloud Pub/Sub | DBT | Dagster | Data Contracts | Data Governance | Data Lineage | Data Observability | Data Pipelines | Data Quality | Data Vault | Data masking | Deidentification | Dimensional Modeling | Docker | ELT | ETL | FHIR R4 | Feast | GCP | Google Cloud | Google Cloud Pub/Sub | HIPAA | HL7 V3 | HL7 v2 | ICD10 | Infrastructure Monitoring | Infrastructure as Code | Integration Testing | Kubernetes | LOINC | MLOps | Prefect | Pub/Sub | Python | Redshift | SNOMED CT | SQL | Schema drift | Snowflake | Streaming Data | Streaming data pipelines | Tecton | Terraform | Unit Testing | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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