Data Engineer for Life Sciences
3 weeks ago
AI Talent Flow is a leader in accelerating startup growth and scaling enterprise solutions. We are seeking a highly skilled Data Engineer to join our team.
Estimated salary: $140,000 - $180,000 per year.
About the Role:
We are looking for an experienced Neo4j expert to work with life sciences and healthcare stakeholders to understand their data needs and identify high-impact use cases for leveraging Neo4j and graph databases.
The successful candidate will design and develop efficient and scalable data models using Cypher (Neo4j query language) and best practices.
Key Responsibilities:
- Partner with life sciences and healthcare stakeholders to understand their data needs and identify high-impact use cases for leveraging Neo4j and graph databases.
- Design and develop efficient and scalable data models using Cypher (Neo4j query language) and best practices.
- Build and maintain robust semantic layers that integrate data from disparate sources within the life sciences and healthcare domains (e.g., clinical trials data, patient records, genomic data).
- Utilize Neo4j features like APOC libraries and procedures to enhance functionality and performance.
- Collaborate with data scientists and analysts to prepare data for analysis and visualization within the Neo4j graph.
- Optimize graph queries for performance and scalability to ensure efficient data retrieval and analysis.
- Monitor and maintain Neo4j deployments for smooth operation and identify potential issues.
- Stay up-to-date on the latest advancements in Neo4j technology and best practices within the life sciences and healthcare industry.
- Document data models and processes for clear communication and knowledge sharing.
Requirements:
- Extensive experience with Neo4j, including Cypher querying, schema design, data modeling, and performance optimization.
- Strong understanding of graph database concepts and their application in various use cases.
- Data Modeling: Experience with data modeling techniques for relational and non-relational databases.
- Familiarity with cloud platforms like AWS, Azure, or GCP for potential Neo4j deployment.
- Version Control Systems: Experience with version control systems like Git for code management and collaboration.
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