Senior Data Engineer

Qube Research & Technologies; Amsterdam; On-site; EUR 90,000 - 130,000; Full time

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 (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT's collaborative mindset which enables us to solve the most complex challenges. QRT's culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

Your future role within QRT:

• 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.

Your present skillset:

• 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.

Nice to have:

• Experience working with market or financial data.
• Knowledge of non-equity asset classes (e.g. futures, fixed income, commodities, FX).
• C++ development experience.
• SQL proficiency.
• Experience with Docker, Kubernetes, and Infrastructure-as-Code (Terraform or CloudFormation).
• Familiarity with Apache Parquet, Apache Arrow, or distributed processing frameworks such as Spark, Ray, or Dask.

QRT is an equal opportunity employer. We welcome diversity as essential to our success.

QRT empowers employees to work openly and respectfully to achieve collective success.

In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.