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Mid LevelFull-timePythonAWSTerraformGraphQLData
Salary Range
$76,500 - $103,500 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Data Engineer to join Quotient Therapeutics, an early-stage company developing a novel genomics platform for drug discovery. This mid-level role involves designing, building, and operating data workflows and services that support complex biological data analysis.
Key Responsibilities
- →Design, implement, and operate robust, scalable data workflows supporting genomics, imaging, and downstream analytics
- →Collaborate closely with scientists and platform stakeholders to understand analytical needs and translate them into durable data models and pipelines
- →Develop and maintain ETL/ELT workflows using modern orchestration frameworks
- →Manage large scientific data assets, including genomic sequence files and histology images
- →Build and operate backend data services, including databases and APIs that expose data to scientists and applications
- →Apply best practices for version control, testing, documentation, and reproducibility
- →Ensure data quality, integrity, and traceability through validation checks and monitoring
- →Continuously improve data infrastructure to support evolving scientific workflows
- →Communicate clearly with stakeholders across engineering and scientific teams
Requirements
- ✓Graduate or post-graduate degree in computer science, bioinformatics, or related field, or equivalent practical experience
- ✓Three years or more of hands-on experience building and operating data pipelines or data platforms
- ✓Strong collaboration skills and a pragmatic mindset suited to an interdisciplinary biotech environment
- ✓Demonstrated ability to learn domain context to better serve scientific users
- ✓Strong proficiency in Python and Linux, with solid software engineering practices
- ✓Proficiency in SQL and working with backend data stores and query engines
- ✓Experience with cloud-based data engineering patterns (AWS preferred)
- ✓Experience with workflow orchestration frameworks
- ✓Experience managing large data assets, including file-based scientific data
- ✓Familiarity with common genomic, histology imaging, and other large scientific data types
- ✓Familiarity with modern DevOps practices, especially infrastructure-as-code
