Senior Data Engineer: Real-Time Quant Trading Platform

Darwin Partners; Brussel; Sur place; EUR 70 000 - 100 000; Plein temps

Résumé du poste

Darwin Partners is building the next generation data platform for real-time algorithmic trading. You will design, deploy and operate data infrastructure powering trading models, signals and market data across multiple markets.

You will collaborate with AI engineers, quantitative developers and traders to ensure data quality, traceability and performance. The role offers an opportunity to industrialise DataOps and MLOps practices in production.

Qualifications

• Five to seven years in Data Engineering or related field.
• Advanced Python skills and strong software fundamentals.
• Experience with real-time data pipelines and production-grade systems.
• Proficient with Kafka, RabbitMQ or similar messaging systems.
• Hands-on with Docker, Kubernetes and cloud environments.

Responsabilités

• Design, build and optimise low-latency data architectures.
• Define foundations to support algorithmic trading and large-scale data processing.
• Select storage, streaming and distributed processing technologies.
• Contribute to architecture standards and best practices.
• Develop, automate and monitor ETL/ELT pipelines.
• Ingest real-time data: prices, trades, positions, market data, signals.
• Ensure scalability, resilience and performance of data pipelines.
• Implement event replay, backfilling, recovery and reconciliation.

Connaissances

Python

C++

Rust

Java

Scala

Software engineering fundamentals

Real-time streaming

Distributed systems

Team collaboration

Production mindset

Outils

Apache Kafka

RabbitMQ

Docker

Kubernetes

TimescaleDB

InfluxDB

ClickHouse

KDB+

AWS

Azure

GCP

Description du poste

Darwin Partners is building the next generation data platform for real-time algorithmic trading. You will design, deploy and operate data infrastructure powering trading models, signals and market data across multiple markets.

You will collaborate with AI engineers, quantitative developers and traders to ensure data quality, traceability and performance. The role offers an opportunity to industrialise DataOps and MLOps practices in production.