Data Engineer with Life Science
Data Engineer with Life Science
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1 Vacancy
Job Description
Job Description:
Key Responsibilities
Data Migration and Integration:
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.
Database Development:
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.
Visualization Tool Integration:
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.
Collaboration and Communication:
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.
Must-Have Qualifications
Database Expertise: Proven experience with relational databases like Oracle and PostgreSQL including design optimization and migration.
Programming Skills: Strong proficiency in Python especially for backend development and data handling. Java is an added advantage.
ETL Development: Expertise in building Extract Transform and Load (ETL) processes to effectively process and migrate assay/compound data.
Integration Experience: Familiarity with integrating data into visualization platforms and crafting modular plugins or interfaces.
Team Collaboration: A demonstrated ability to work with globally distributed teams across time zones to deliver complex projects. Nice-to-Have Skills
Data Engineering Knowledge: Skills in building data pipelines data modeling and working with modern cloud platforms such as AWS or GCP.
Visualization Expertise: Experience with visualization tools such as Vortex or D360.
Domain Knowledge: Familiarity with laboratory workflows assay data compound data or related pharmaceutical/life sciences data.
Plugin Development Tools: Experience with APIs or SDKs for creating custom visualization tool integrations.
DevOps Practices: Familiarity with Docker Kubernetes or CI/CD pipelines to streamline development and deployment. Key Attributes
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.
Location (Onsite from Day 1) : -
- San Francisco CA ( 4 days from Office). Candidates must reside San Francisco CA or be open to relocate
- Candidates should be authorized to work in the United States.
Educational Qualifications: -
- Engineering Degree BE/ME/BTech/MTech/BSc/MSc.
- Technical certification in multiple technologies is desirable.
Employment Type
Full-time
