Overview
On Site
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - 12 Month(s)
Skills
AWS
Devops
Python
PostgreSQL
ETL
pharmaceutical/life sciences
Job Details
Job Title: Data Engineer with Life Science
Location: San Francisco, CA ( 4 days from Office)
Job Type: Contract
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 Google Cloud Platform.
- 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.
Educational Qualifications
- Engineering Degree BE/ME/BTech/MTech/BSc/MSc.
- Technical certification in multiple technologies is desirable.
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