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Zifo

Specialist scientific informatics services for science

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USA$100k - $130kRemote

About the Job

Requirements

  • Strong Python development experience, including PDF and document parsing libraries such as PyMuPDF, pdfplumber, or unstructured.io.
  • Advanced PostgreSQL-compatible SQL skills, including Amazon Aurora, with experience in schema design, migrations, query optimization, and indexing strategies for large clinical datasets.
  • Hands-on experience with Neptune, Neo4j, or similar graph databases; proficiency in SPARQL or Cypher; and experience with ontology and knowledge graph modeling for biomedical entities.
  • Experience with AWS services including Aurora PostgreSQL, S3, Lambda, Step Functions, SQS/SNS, and IAM, particularly for data pipeline orchestration.
  • Experience with PDF text extraction, document section classification, and named entity recognition for clinical or biomedical text; familiarity with embedding models and vector stores such as OpenSearch, pgvector, or Pinecone.
  • Experience building data-serving APIs using FastAPI, including asynchronous programming patterns and backend integration.
  • Experience preparing data for LangChain or LangGraph applications and designing RAG pipelines, including chunking, retrieval, reranking, and prompt-data integration.
  • Experience with Airflow, Prefect, AWS Step Functions, Temporal, or similar workflow orchestration tools, including designing multi-stage DAGs with dependency management, retry logic, monitoring, and error handling.
  • Experience with Terraform or AWS CDK, Docker, and Git, including automated pipeline testing and deployment on AWS.
  • Understanding of clinical trial structure, including protocol sections such as objectives, endpoints, eligibility criteria, study design, and statistical considerations.
  • Awareness of regulatory data integrity requirements, including 21 CFR Part 11, EU Annex 11, and ALCOA+ principles.

Responsibilities

  • Design, build, and operate data infrastructure for a clinical trial design platform that extracts insights from clinical protocols, regulatory documents, and published articles to accelerate trial design decisions.
  • Own pipelines that ingest, parse, transform, and serve clinical data, from raw PDF extraction through structured storage in Aurora and GraphDB to curated knowledge for LangGraph-based agentic AI workflows.
  • Build ingestion pipelines for clinical trial protocols, ICF documents, SmPCs, CSRs, and published articles from PubMed, CTIS, and ClinicalTrials.gov, handling PDF parsing, text extraction, and structured data normalization.
  • Design and implement data models in Amazon Aurora and GraphDB to represent trial design entities and their relationships, including endpoints, eligibility criteria, study arms, interventions, and therapeutic areas.
  • Develop embedding and vectorization pipelines to prepare extracted clinical text for RAG-based retrieval in LangGraph agentic workflows, including chunking strategies, metadata enrichment, and vector store population.
  • Build and maintain ETL/ELT workflows that transform unstructured clinical content into queryable, linked data across relational and graph stores.
  • Implement data quality validation for clinical data, including protocol section classification accuracy, entity extraction completeness, and cross-reference integrity for NCT IDs, EudraCT numbers, and MeSH terms.
  • Build data-serving APIs using Python and FastAPI to expose curated datasets to the Angular frontend and LangGraph agent layer.
  • Set up data lineage tracking and audit trails to support regulatory traceability of AI-generated trial design recommendations.

Desired Qualifications

  • Familiarity with clinical data standards or terminologies such as MeSH, MedDRA, SNOMED, ATC codes, and CDISC.
  • Experience with biomedical knowledge graphs, such as linking drugs to targets, diseases, and trials.
  • Prior work with PubMed/MEDLINE data, the ClinicalTrials.gov API, or EMA/CTIS data.
  • Experience with Apache Spark or Databricks for batch processing of large document corpora.
  • Experience with dbt for transformation layer management over Aurora.

About the Company

Zifo

Specialist scientific informatics services for science

Zifo provides tailored scientific informatics services across Laboratory/R&D, Manufacturing, and Trial operations to help science-driven organizations discover, develop, manufacture, and test products for global health. It partners with clients to assess needs, design and implement data-driven solutions, and manage ongoing operations using consulting, development, and managed services, leveraging cloud, HPC, data modeling, and instrument data. It differentiates itself with end-to-end informatics capabilities and deep domain knowledge, from transformation coaching to validation and custom integrations, all aimed at supporting research, development, manufacturing, and trials. Its goal is to empower customers to push the boundaries of science and technology while advancing global health and wellbeing.

Company size
1,001-5,000
Company stage
Growth Equity (Non-Venture Capital)
Total funding
$250M
Headquarters
New York, NY
Founded
2008

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