Senior Data Platform Engineer - Python, AWS, Airflow

Qube Research & Technologies; Amsterdam; On-site; EUR 90,000 - 140,000; Full time

Job summary

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager. You will design, build, and operate the data platform powering quantitative research and backtesting, developing production-grade Python applications to acquire, process, validate, and distribute market data.

You will build scalable data pipelines using Apache Airflow on AWS, ensuring data quality and observability across critical production pipelines, while collaborating closely with researchers,

Qualifications

• 5+ years building production-grade data platforms.
• Strong Python software engineering experience.
• Hands-on with Apache Airflow or similar.
• Experience with AWS services (S3, EC2, Batch, IAM, CloudWatch).
• Strong Linux skills and production systems support.
• Focus on data quality, validation, and observability.

Responsibilities

• Design, build, and operate the data platform for research and backtesting.
• Develop production-grade Python applications for data acquisition and processing.
• Create scalable data pipelines with Airflow across AWS and internal infra.
• Ensure data quality, validation, and observability in production.
• Collaborate with researchers, software engineers, and infra teams to onboard datasets.
• Drive engineering best practices for quality, automation, and scalability.

Skills

Python

Airflow

AWS

Linux

Data quality

Observability

Distributed processing

Collaboration

Tools

Docker

Kubernetes

Terraform

CloudFormation

Job description

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager. You will design, build, and operate the data platform powering quantitative research and backtesting, developing production-grade Python applications to acquire, process, validate, and distribute market data.

You will build scalable data pipelines using Apache Airflow on AWS, ensuring data quality and observability across critical production pipelines, while collaborating closely with researchers,