Data Platform Engineer - Database & Infrastructure

Qube Research & Technologies (qrt)
Paris, France
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Airflow Amazon Web Services Amazon S3 Backup Devices Bash Shell Computer Programming Databases Continuous Integration Data as a Services Information Engineering Data Infrastructure Dataspaces
+22 more
Linux DevOps Distributed Data Store Failover Identity and Access Management Python (Programming Language) Online Analytical Processing Operational Databases Prometheus Parquet Scripting Grafana Apache Spark Data Lakes Kubernetes Infrastructure Automation Frameworks Apache Kafka Data Management Vertica Terraform Data Pipelines Docker

Job description

We are looking for an experienced Data Platform Engineer to join our DevOps team in Paris. This role is fully on-site, with a strong focus on ensuring the reliability and scalability of our production data infrastructure.

Your future role within QRT:

This role sits at the intersection of data engineering and infrastructure engineering, focused on building reliable, scalable, and high-performance data platforms.

Your responsibilities will include:

  • Ensuring reliability and performance of production data systems (ClickHouse, CockroachDB, Trino, etc.)
  • Designing and operating database clusters on Kubernetes (via operators)
  • Building and maintaining data pipelines (ingestion, transformation, replication)
  • Driving Infrastructure-as-Code practices (Terraform, Helm)
  • Operating storage and data platforms across on-prem (VAST) and AWS (S3, EMR, MSK, RDS, EKS)
  • Managing Docker images and CI/CD workflows for data services
  • Defining and maintaining AWS IAM policies and permissions
  • Troubleshooting across the stack (databases, OS, storage, networking)
  • Implementing observability (metrics, alerting, capacity planning)
  • Collaborating with engineering, data, and research teams

Requirements

  • 5+ years in DevOps, Data Platform Engineering, or similar
  • Experience with distributed data systems in production (e.g. ClickHouse, Trino, EMR)
  • Strong Kubernetes experience (stateful workloads, Helm, operators)
  • Solid Infrastructure-as-Code experience (Terraform, Helm, etc.)
  • Good knowledge of AWS data ecosystem (S3, EKS, EMR, MSK, RDS)
  • Strong understanding of AWS IAM and security best practices
  • Hands-on experience with Docker and CI/CD pipelines
  • Experience with data pipelines (Kafka, Spark, Airflow, etc.)
  • Strong Linux fundamentals and scripting (Python and/or Bash)
  • Understanding of database reliability (replication, backups, failover)

Nice to have:

  • OLAP / high-throughput systems experience
  • Experience with VAST Data or similar storage systems
  • Familiarity with Iceberg, Delta Lake or Hudi
  • Observability tools (Prometheus, Grafana, OpenTelemetry)
  • GitOps tools (ArgoCD, Flux)
  • CKA or strong Kubernetes expertise
  • Programming in Go, Rust, or Python
  • Knowledge of Parquet/Arrow and query engines
  • AWS certifications

Benefits & conditions

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.

About the company

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.

We operate one of the most demanding data infrastructures in finance, supporting mission-critical distributed systems across multiple database and streaming platforms, with strict requirements around availability and performance. Our environment spans both on-prem infrastructure and AWS, with a strong focus on standardization, automation, and Kubernetes-based orchestration.

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