Senior Software Engineer, Data Platform

Profluent Bio

Senior Software Engineer designing, building, and scaling Profluent's AI data platform for protein engineering campaigns. Collaborating with cross-disciplinary teams to ensure data integrity and accessibility.

Posted 5/12/2026full-timeEmeryville • California • 🇺🇸 United StatesSenior💰 $170,000 - $220,000 per yearWebsite

Tech Stack

Tools & technologies

BigQueryCloudGoogle Cloud PlatformPostgresPython

About the role

Key responsibilities & impact

Design, build, and maintain scalable data infrastructure for protein engineering campaigns, including ingestion, transformation, validation, storage, and retrieval of large scientific datasets
Develop secure data pipelines for internal and partner-generated data, with strong attention to access control, data siloing, provenance, auditability, and compliance with data use restrictions
Own core components of Profluent’s data warehouse and data platform, using Python, GCP, PostgreSQL, BigQuery, and related cloud-native technologies
Build systems that transform raw experimental, computational, and partner data into structured, reliable, analysis-ready and model-ready datasets
Establish best practices for data modeling, metadata management, data quality checks, schema evolution, versioning, and documentation
Collaborate with ML engineers, computational biologists, data scientists, and program stakeholders to understand data requirements and translate them into scalable technical systems
Improve engineering quality through thoughtful system design, code review, testing, CI/CD, observability, and maintainable development workflows
Contribute to architectural decisions for how Profluent stores, secures, organizes, and uses data across programs and partnerships

Requirements

What you’ll need

5+ years of software engineering, data engineering, or data platform experience
Strong proficiency in Python and modern software development practices, including git, testing, code review, CI/CD, and production deployment
Experience designing and operating production data pipelines, data warehouses, and data models at scale
Hands-on experience with cloud platforms, preferably GCP, and technologies such as BigQuery, PostgreSQL, object storage, workflow orchestration, and containerized services
Strong understanding of data security, access control, data partitioning or siloing, audit logging, and managing sensitive or restricted datasets
Experience working with complex, heterogeneous datasets and building systems that make them reliable, discoverable, and usable
Ability to work independently, make sound technical decisions, and drive projects from ambiguous requirements to production systems
BS, MS, or PhD in Computer Science, Engineering, Data Science, Bioinformatics, or a related technical field, or equivalent practical experience

Benefits

Comp & perks

Competitive compensation package with equity participation
401(k) with a strong employer match
Comprehensive benefits including health/dental/vision insurance
Generous PTO policy and commitment to work-life balance
Professional development opportunities in a cutting-edge field at the intersection of AI and biology

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Pythondata engineeringdata pipelinesdata warehousesdata modelingmetadata managementdata quality checksschema evolutionversioningproduction deployment

Soft Skills

collaborationindependent worktechnical decision makingproject managementattention to detail

Certifications

BS in Computer ScienceMS in Computer SciencePhD in Computer ScienceBS in EngineeringMS in EngineeringPhD in EngineeringBS in Data ScienceMS in Data SciencePhD in Data ScienceBS in Bioinformatics