Senior Clinical Data Engineer - AI Pipelines & GraphDB

Zifo; United States; Vor Ort; USD 130.000 - 165.000; Vollzeit

Benefits dieser Stelle

Medical insurance

Dental & Vision

401(k) with company match

Life insurance

Flexible spending accounts

Paid vacation

Zusammenfassung

Zifo is seeking a data-focused engineer to design, build, and operate ingestion pipelines for clinical data, transforming unstructured content into structured, queryable data in Aurora and GraphDB. You will shape data models for endpoints, eligibility, and study arms, and develop embedding pipelines for LangGraph-based AI workflows.

You will implement ETL/ELT pipelines, validate data quality, and expose curated datasets via FastAPI APIs to support an Angular frontend and LangGraph agent layers.

Qualifikationen

• Strong Python development experience with PDF/text extraction libraries.
• Advanced PostgreSQL/Aurora SQL, with large dataset optimization.
• Hands-on with graph databases and knowledge graph modeling.
• Experience building data pipelines for LangGraph/LangChain workflows.

Aufgaben

• Design, build, and operate ingestion pipelines for clinical data (protocols, CSRs, PubMed).
• Model data in Aurora and GraphDB for trial design entities and relationships.
• Develop embedding/vectorization for RAG retrieval in agentic workflows.
• Create ETL/ELT workflows across relational and graph stores.
• Implement data quality validation and lineage/audit trails.

Kenntnisse

Python development

PostgreSQL/Aurora

Graph databases (Neptune/Neo4j)

Data modeling (relational + graph)

ETL/ELT design

PDF/text extraction

NFT/Vector embedding pipelines

FastAPI/backend services

AWS data pipelines

Ausbildung

Bachelor's degree in CS/BI/ID or related

Tools

Neo4j/Neptune

SPARQL/Cypher

OpenSearch/pgvector/Pinecone

Docker

Terraform/AWS CDK

Jobbeschreibung

Zifo is seeking a data-focused engineer to design, build, and operate ingestion pipelines for clinical data, transforming unstructured content into structured, queryable data in Aurora and GraphDB. You will shape data models for endpoints, eligibility, and study arms, and develop embedding pipelines for LangGraph-based AI workflows.

You will implement ETL/ELT pipelines, validate data quality, and expose curated datasets via FastAPI APIs to support an Angular frontend and LangGraph agent layers.