Data Engineer
Core
Build and manage cloud-native ETL/ELT pipelines and data platforms for the life sciences industry.
Role type
Data Engineer
Builds
Cloud-native data pipelines, data mesh/fabric architectures, and automated data quality systems
Domain
Life sciences / Healthcare
Deliverable
production ML models
Required skills
Python, SQL, PySpark, dbt, Databricks, CI/CD automation, Terraform, DataOps principles, data quality frameworks, observability tools
Preferred skills
Snowflake, data lineage tools, Bash/PowerShell, dimensional modeling, GxP regulations, non-relational databases
Technologies
Databricks, dbt, PySpark, Azure, AWS, GCP, GitHub Actions, Azure DevOps, Terraform
Responsibilities
Build and manage ETL/ELT pipelines; Contribute to scalable data platforms across cloud environments; Implement and maintain CI/CD workflows; Apply DataOps principles for pipeline versioning and testing; Integrate automated data quality checks; Ensure data observability via logging and metrics; Collaborate on infrastructure as code; Connect and orchestrate data ingestion from APIs and databases
Seniority
Mid-level to Senior, hands-on IC