Platform Data Engineer

PathGen; Singapore; Hybrid; SGD 90,000 - 130,000; Full time

Benefits offered by this job

Competitive salary

Paid leave

Hybrid-friendly work pattern

Job summary

PathGen seeks a pragmatic Data Engineer to handle diverse data types — from natural language to geospatial and biological data — and build robust data pipelines for health applications. You will join a mission-driven team collaborating with leading institutions in APAC and beyond.

Ideal candidates combine strong Python/data skills with experience deploying pipelines, containers, and cloud workflows, enabling scalable ML infrastructure and reliable data products.

Qualifications

• 2+ years of experience deploying and maintaining data pipelines in Python.
• Strong Python and data skills.
• Experience with Docker, container orchestration, and cloud deployments (AWS preferred).
• Experience with data engineering workflows (Airflow, Prefect, Kafka, K8s).
• Strong experience with data engineering best practices.

Responsibilities

• Build and monitor scalable data ingestion pipelines for structured datasets (e.g., genomic repositories, scientific literature, climactic datasets, socio-economics).
• Automate ETL processes, pre-processing workflows, and model lifecycle operations (kafka, airflow).
• Collaborate with bioinformatics experts to ensure data quality and traceability.
• Assist with deployment and maintenance of machine learning models using FastAPI and containerized microservices.
• Manage model inference endpoints and batch inference workflows (e.g., AWS Batch or K8s).
• Implement CI/CD pipelines for ML workflows using tools like GitHub Actions, Docker, Terraform.

Skills

Python data pipelines

Docker

Cloud AWS

Airflow / Kafka / K8s

Data engineering best practices

Tools

Docker

Kubernetes

AWS

Terraform

GitHub Actions

Job description

We are looking for a pragmatic and technically skilled Data Engineer with a focus on engineering for diverse data types - including; natural language, geospatial and biological data. This role is ideal for someone with experience in building robust data pipelines to support health or biological applications.

This is a truly exciting opportunity to work with leading global institutions, government agencies, and country partners at the intersection of AI, public health & pathogen genomics to generate positive social impact whilst leading on cutting edge AI initiatives in APAC and the wider world!

Responsibilities:

• Build and monitor scalable data ingestion pipelines for structured datasets (e.g., genomic repositories, scientific literature, climactic datasets, socio-economics).
• Automate ETL processes, pre-processing workflows, and model lifecycle operations (kafka, airflow)
• Collaborate with bioinformatics experts to ensure data quality and traceability.
• Assist with deployment and maintenance of machine learning models using FastAPI and containerized microservices.
• Manage model inference endpoints and batch inference workflows (e.g., AWS Batch or K8s).
• Implement CI/CD pipelines for ML workflows using tools like GitHub Actions, Docker, Terraform

Essential Qualifications:

• 2+ years of experience deploying and maintaining data pipelines in python.
• Strong Python and data skills
• Experience with Docker, container orchestration, and cloud deployments (AWS preferred).
• Experience with data engineering workflows (e.g., Airflow, Prefect, Kafka, K8s).
• Strong experience with data engineering best practices.

Bonus Qualifications:

Experience or familiarity with one or more of the following areas will be highly advantageous:

• Domain expertise or strong interest in biological or geospatial data

Desired Personal Attributes:

• Start-up mentality (flexible & pragmatic)
• Strong collaboration skills in multi-disciplinary environments.
• Systems thinking and a bias toward reliability & scalability.
• Ability to design practical, maintainable data & ML infrastructure.

What We Offer:

• A mission-driven environment focused on improving global public health.
• Opportunities to work on high-impact problems in AI and pathogen genomics.
• A flexible and collaborative work culture with a commitment to innovation.
• Low bureaucracy - direct ownership of the product, no ticket-factory work.
• Competitive salary & paid leave
• Hybrid-friendly work pattern

Join us to help operationalize the future of genomic intelligence and deploy real-world AI tools that matter.