Senior Data Infrastructure Engineer – Real-Time, Large-Scale

Qube Research & Technologies; Paris; Sur place; EUR 90 000 - 140 000; Plein temps

Avantages offerts par ce poste

Restaurant d'entreprise

Indemnités de stage/alternance

Résumé du poste

Qube Research & Technologies is a global quantitative and systematic investment manager. You will join the data infrastructure team dedicated to the ingestion, processing and serving of large amounts of data at scale.

Data is at the heart of everything QRT does, with exponentially growing needs. The candidate will push the edges of one of the most demanding data systems in the world, working on real time pub sub and sharded databases.

Responsabilités

• Design, review and implement services and clients.
• Triage and investigate system issues and debug/track/resolve to ensure the robustness of our operations.
• Consistently apply and help evolve coding best practices: review peer code, lead or participate in design reviews, with a focus on code quality, testability, and efficiency.
• Work with stakeholders and customers to understand their business needs, technical needs, and react accordingly.
• Excellent knowledge of algorithms and data structures, as well as system design.
• An overall understanding of the big data landscape, knowing the design, strengths and drawbacks of tools such as Elasticsearch, Kafka, BigTable, Cassandra etc…
• Excellent communication and writing skills, with the ability to work effectively across teams and departments.

Connaissances

Algorithms & data structures

System design

Multithreading

Asynchronous I/O

Communication skills

Outils

Elasticsearch

Kafka

BigTable

Cassandra

Rust

C++

Go

Java

Description du poste

Qube Research & Technologies is a global quantitative and systematic investment manager. You will join the data infrastructure team dedicated to the ingestion, processing and serving of large amounts of data at scale.

Data is at the heart of everything QRT does, with exponentially growing needs. The candidate will push the edges of one of the most demanding data systems in the world, working on real time pub sub and sharded databases.