We are seeking a skilled Data/Cloud Engineer to provide platform-side support and pipeline standardization for advanced Causal Biology research within a global biopharmaceutical organization.
In this role, you will empower scientific teams to effectively leverage the Omics Workbench platform, optimize data pipelines, diagnose complex cloud-level issues, and contribute to cutting-edge AI/ML-assisted pipeline development workflows.
Key Responsibilities
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Platform Enablement: Provide platform-level support enabling scientific teams to effectively utilize the Omics Workbench and standardize data processing pipelines.
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Pipeline Standardization: Enforce architectural standards, best practices, and reusable design patterns across biology-focused data pipelines.
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Troubleshooting \& RCA: Investigate, diagnose, and resolve pipeline and platform-level incidents, conducting Root Cause Analysis (RCA) in collaboration with scientific and cloud teams.
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AI/ML Pipeline Integration: Contribute to the development, documentation, and iterative improvement of processes where pipelines are generated, reviewed, and released using AI/ML tools.
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Platform Capabilities: Support adjacent cloud platform capabilities to enhance analytical research workflows as capacity permits.
Requirements (Must-Have)
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Python Proficiency: Strong, demonstrable experience writing production-quality Python code, including unit testing and code review practices.
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Google Cloud Platform (GCP): Solid hands-on experience building and managing cloud infrastructure/services on GCP.
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Pipeline Development: Practical background in developing, debugging, and optimizing data or analytical pipelines in cloud environments.
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English Fluency: Excellent verbal and written English communication skills to engage directly and independently with research scientists and project stakeholders.
