Data Engineer at StarRez designing and maintaining data pipelines for analytics. Collaborating with teams to drive data quality and insights across the product.
About the role
- Staff Data Engineer designing automated data infrastructure for early cancer detection technologies at GRAIL. Collaborating with engineers and scientists to streamline operations and ensure data quality.
Responsibilities
- Be a part of a highly collaborative team focused on delivering value to cross-functional partners by designing, deploying, and automating secure, efficient, and scalable data infrastructure and tools—reducing manual efforts and streamlining operations.
- Help model Grail data to ensure it follows FAIR principles (Findable, Accessible, Interoperable, and Reusable).
- Drive the design, deployment, and automated delivery of data infrastructure, standardized data models, datasets, and tools.
- Integrate automated testing and release processes to improve the quality and velocity of software and data deliveries.
- Collaborate with cross-functional teams—ranging from Research to Clinical Lab Operations to Software Engineering—to provide comprehensive data solutions from conception to delivery.
- Ensure all software and data meet high standards for quality, clinical compliance, and privacy.
- Mentor fellow engineers and scientists, promoting best practices in software and data engineering.
Requirements
- B.S. / M.S. in a quantitative field (e.g., Computer Science, Engineering, Mathematics, Physics, Computational Biology) with 8+ years of related industry experience, or Ph.D. with at least 5 years of related industry experience or equivalent.
- Extensive experience developing with relational databases, data modeling principles, data pipeline tools, and workflow engines (e.g., SQL, DBT, Apache Airflow, AWS Glue, Spark).
- Extensive experience with DevOps practices, including CI/CD pipelines, containerized deployment (e.g., Kubernetes), and infrastructure-as-code (e.g., Terraform).
- Experience supporting data science and machine learning data pipelines, preferably in the context of biological data analysis and using Python.
- Ability to embrace uncertainty, navigate ambiguity, and collaborate with product teams and stakeholders to refine requirements and drive toward clear engineering objectives and designs.
- You are a strong written and verbal communicator and can adapt your communication style and the level of detail to your audience.
Benefits
- flexible time-off
- 401k with a company match
- medical plans
- dental plans
- vision plans
- mindfulness offerings
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