Senior Data Platform Engineer for Quant Research

Qube Research & Technologies

Amsterdam

On-site

EUR 90,000 - 130,000

Full time

14 days+

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Job summary

Qube Research & Technologies invites engineers to design, build, and operate a scalable data platform powering quantitative research and backtesting.

You will develop Python applications to acquire, process, validate, and distribute market data, and you will build automated pipelines using Airflow and AWS Batch across AWS. Collaboration with researchers and infrastructure teams is essential and you will drive software quality and automation.

Qualifications

  • 5+ years of experience building production-grade data platforms or large-scale data processing systems.
  • Strong Python software engineering experience.
  • Hands-on experience with Apache Airflow or similar workflow orchestration platforms.
  • Experience with AWS services including S3, EC2, AWS Batch, IAM, CloudWatch, and cloud SDKs.
  • Strong understanding of data quality, validation, testing, monitoring, and observability.
  • Good understanding of distributed data processing concepts.
  • Strong Linux skills and experience developing and supporting production systems.
  • Excellent problem-solving skills with the ability to collaborate effectively across research, engineering, and infrastructure teams.

Responsibilities

  • Design, build, and operate the data platform powering quantitative research and backtesting.
  • Develop production-grade Python applications to acquire, process, validate, and distribute market and reference data.
  • Build and operate scalable, automated data pipelines using technologies such as Apache Airflow and AWS Batch across AWS and QRT's compute infrastructure.
  • Ensure data quality, validation, reconciliation, and observability across critical production pipelines.
  • Design systems that efficiently process large-scale datasets while supporting compute-intensive research workloads.
  • Collaborate closely with quantitative researchers, software engineers, and infrastructure teams to accelerate dataset onboarding and improve research productivity.
  • Drive engineering best practices with a strong focus on software quality, automation, scalability, and operational excellence.

Skills

Python
Airflow
AWS
Data quality
Observability
Linux
Collaboration
Software engineering

Tools

Docker
Kubernetes
Terraform
CloudFormation
Parquet
Arrow
Spark
Dask

Job description

Qube Research & Technologies invites engineers to design, build, and operate a scalable data platform powering quantitative research and backtesting.

You will develop Python applications to acquire, process, validate, and distribute market data, and you will build automated pipelines using Airflow and AWS Batch across AWS. Collaboration with researchers and infrastructure teams is essential and you will drive software quality and automation.

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