Data Engineer with Life Science

TalentOla • San Francisco, CA

4d • Onsite

About The Position

We are seeking a Data Engineer with a background in Life Sciences to join our team. The role involves migrating assay and compound data from legacy systems, implementing ETL pipelines, developing and maintaining relational databases, and integrating data into visualization tools. You will collaborate closely with scientific teams in Europe and other stakeholders to deliver user-centric solutions. This position requires strong database expertise, proficiency in Python, and experience with ETL processes and data integration.

Requirements

• Proven experience with relational databases like Oracle and PostgreSQL, including design, optimization, and migration.
• Strong proficiency in Python, especially for backend development and data handling.
• Expertise in building Extract, Transform, and Load (ETL) processes to effectively process and migrate assay/compound data.
• Familiarity with integrating data into visualization platforms and crafting modular plugins or interfaces.
• A demonstrated ability to work with globally distributed teams across time zones to deliver complex projects.
• Strong analytical and problem-solving skills with attention to detail.
• Excellent communication skills to bridge gaps between scientific and technical teams.
• Highly adaptive and able to manage competing priorities in a dynamic, fast-paced environment.
• Self-motivated and able to independently drive progress while collaborating with globally distributed teams.

Nice To Haves

• Skills in building data pipelines, data modeling, and working with modern cloud platforms such as AWS or GCP.
• Experience with visualization tools such as Vortex or D360.
• Familiarity with laboratory workflows, assay data, compound data, or related pharmaceutical/life sciences data.
• Experience with APIs or SDKs for creating custom visualization tool integrations.
• Familiarity with Docker, Kubernetes, or CI/CD pipelines to streamline development and deployment.
• Java is an added advantage.
• Technical certification in multiple technologies is desirable.

Responsibilities

• Migrate assay and compound data from legacy systems into other architectures, ensuring data integrity and security.
• Implement robust ETL pipelines for processing and integrating data efficiently from multiple sources.
• Design, develop, and maintain scalable and high-performing relational databases (e.g., Oracle, PostgreSQL) to host and manage experimental and prediction data.
• Optimize database structures for querying, storage, and scalability.
• Collaborate with teams to integrate data into existing visualization tools and frameworks.
• Develop and enhance plugins for visualization tools to deliver interactive and meaningful insights for scientific teams.
• Work closely with pRED teams in Europe, ensuring alignment in goals and timelines.
• Collaborate with scientists, data engineers, and software developers to define requirements and deliver user-centric solutions.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level