(Senior) Data Engineer – Healthcare

About PAICON Cloud GmbH

PAICON Cloud GmbH is a Heidelberg-based medical data provider. We harmonize real-world health data from providers around the world into a global dataset. The data covers multiple modalities on various disease entities. Our flagship product, PaiX Navigator, generates actionable insights for pharma, biotech and AI companies worldwide.

We are hiring a hands-on senior engineer to integrate data from our global partners into the PaiX ecosystem. Data integration is the core of the role; agentic AI is how we build it faster and more reliably. You will map external data to our internal model, informed by HL7 FHIR, and keep it de-identified, secure and compliant. We are a small, pragmatic team and iterate fast.

What you'll own

• Partner onboarding through to production ingestion: gap analysis, field-level mapping and clear data requests to providers

• Reconciling patient metadata across sources

• Data dictionaries, versioned mappings, source-to-target lineage and audit trails, so every transformation and quality decision is traceable

• Ongoing data quality and the evolution of our PostgreSQL database

• Evaluating AI-assisted extraction and mapping against reference data, with human review for uncertain output

Must-have skills

1. Data Engineering (core)

• Strong SQL skills: design, evolve and refactor schemas, including migrations, query tuning and compatibility with existing applications

• Python for data pipelines, understand and comfortably work with Linux systems

• Has built and run production data pipelines with automated tests, logging, retries, idempotent processing and failure recovery

2. Health data standards

• HL7 FHIR basics; mapping external data to an internal model informed by FHIR

• Basic understanding on clinical terminologies such as ICD-10, ICD-O-3, LOINC, HPO, RxNorm

3. Privacy and security

• De-identification that keeps clinical relationships and time intervals intact, with traceable rules; GDPR, access control and secure credential handling

4. AI-native working

• Uses AI coding agents day to day (e.g. Claude Code, Codex, Cursor), has built LLM or agent workflows with tool use and RAG, and validates their output against reference data; keen to go deeper into agentic orchestration

Nice-to-have skills

• Genomics (VCF/BAM, bcftools or pysam, R) or digital pathology (whole-slide images)

• Graph databases: Neo4j/Cypher or RDF/SPARQL, ontology modelling

• Docker; simple CI/CD;

• Background in bioinformatics or biomedical informatics

• Experience in using AWS cloud infrastructures

Soft skills

• Turns messy partner deliveries into clear gap reports and action lists

• Communicates well with medical, engineering and commercial colleagues

• Independent and hands-on; suits a small team

• Fluent English, our working language

• Picks the simplest solution that works: plain Python, simple queues, S3 and RDS before heavy platforms