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2027 – Internship, Data Engineering

Hong Kong, Singapore

Pay
Pay not listed
Work setting
Not stated
Employment
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What you’ll work on

Full posting
  • Design and implement data stores and APIs

  • Build production-ready datasets for researchers and traders

  • Build and maintain real-time and batch data ingestion and serving infrastructure

  • Monitor data processes

  • Source and evaluate new datasets for trading desks

From the employer’s posting
You’ll design and implement data stores and APIs
build production-ready datasets that researchers and traders can use effectively
Build and maintain the infrastructure used to ingest, process and serve data across our research environment.
monitor data processes
Source and evaluate new datasets based on priorities from our trading desks.

What you’ll bring

All qualifications

Core experience

  • Penultimate or final-year student on a bachelor's or master's degree
  • Experience with Python
  • Grounding in algorithms, data structures, parallel and object-oriented programming
  • Rigorous, structured approach to unfamiliar problems
  • Clear communication and direct collaboration with researchers, traders and engineers
Qualification wording
Penultimate or final-year students completing a bachelor’s or master’s degree
Experience with Python and an interest in using software to solve data or infrastructure problems.
A good grounding in areas such as algorithms, data structures, parallel programming and object-oriented programming.
A rigorous, structured approach to analysing unfamiliar problems and working towards practical solutions.
Able to communicate clearly and collaborate directly with researchers, traders and engineers.
Education & alternatives
Programme duration: from 3 to 6 months, starting in 2027. Who qualifies: Penultimate or final-year students completing a bachelor’s or master’s degree Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager operating across liquid asset classes and markets worldwide. Our approach to investing is scientific: we bring together data, research, technology and trading expertise to develop and run systematic strategies.

Tools in this posting

  • Python
  • SQL
  • NoSQL
Source — Tool mentions in context
- Computer science foundations – A good grounding in areas such as algorithms, data structures, parallel programming and object-oriented programming. - Programming – Experience with Python and an interest in using software to solve data or infrastructure problems. - Engineering interests – An interest in software engineering, infrastructure or data engineering, particularly where performance and reliability matter.
Preferred qualifications (a plus): - Knowledge of SQL or NoSQL databases. - Experience with front-end development.

Posting record

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First seen by us
Aug 26, 2026 · 66 days ago
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Last seen by us
Nov 1, 2026

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Job description

View original posting ↗

Location: Hong Kong, Singapore

Programme duration: from 3 to 6 months, starting in 2027.   

Who qualifies: Penultimate or final-year students completing a bachelor’s or master’s degree 

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager operating across liquid asset classes and markets worldwide. Our approach to investing is scientific: we bring together data, research, technology and trading expertise to develop and run systematic strategies. 

Technology and data are central to how QRT works. Over the years, we have built a global research and execution platform spanning geographies, asset classes and trading horizons, from ultra-low-latency systems to large-scale research, analytics and data infrastructure. We invest heavily in engineering, automation and scalable systems because better technology allows us to test ideas faster, operate more reliably and tackle harder problems. 

Our internships are designed to give students meaningful experience of that work. You’ll join a team, contribute to real projects and work alongside engineers, researchers and traders on problems that matter to our research and trading activities. The environment is technical and collaborative, with plenty of scope to ask questions, test ideas and take ownership. 

Your future role at QRT 

As part of QRT’s data teams, you’ll work on the systems and datasets behind quantitative research and trading. You’ll collaborate closely with traders, researchers and engineers, tackling problems across data acquisition, engineering and platform design. 

Throughout the recruitment process, we’ll consider your skills and interests alongside the problems our teams are working on. Depending on the strongest fit, your internship may focus on one of the following areas: 

  • Quantitative Data Analyst – Source and evaluate new datasets based on priorities from our trading desks. You’ll explore how new data can support research, manage sourcing projects from acquisition through to design, and work with Data Engineers to bring useful datasets into production at scale. 
  • Data Engineer – Work with large datasets across QRT’s research and trading platforms. You’ll design and implement data stores and APIs, monitor data processes and build production-ready datasets that researchers and traders can use effectively. 
  • Data Platform Engineer – Build and maintain the infrastructure used to ingest, process and serve data across our research environment. You’ll work on real-time and batch workflows, with a focus on reliability, latency and efficiently handling growing volumes of complex data. 

Your present skillset 

  • Computer science foundations – A good grounding in areas such as algorithms, data structures, parallel programming and object-oriented programming. 
  • Programming – Experience with Python and an interest in using software to solve data or infrastructure problems. 
  • Engineering interests – An interest in software engineering, infrastructure or data engineering, particularly where performance and reliability matter. 
  • Systems – Curious about high-performance, real-time systems and interested in developing a deeper understanding of how they support trading. 
  • Problem solving – A rigorous, structured approach to analysing unfamiliar problems and working towards practical solutions. 
  • Communication – Able to communicate clearly and collaborate directly with researchers, traders and engineers. 
  • Approach – Self-motivated and keen to develop autonomy as you learn. 

Preferred qualifications (a plus): 

  • Knowledge of SQL or NoSQL databases. 
  • Experience with front-end development. 
  • An interest in financial markets and/or algorithmic trading. 

Interviewing  

  • Application – Submit your application online. We review applications on a rolling basis. 
  • Technical Assessment – Selected candidates will complete a coding challenge focused on core programming and problem-solving skills. 
  • Interviews – Shortlisted candidates will take part in interviews, either on-site or via Microsoft Teams. We’ll explore your technical foundations, how you approach unfamiliar problems and how you work with others. 

 

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. 

Source details

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Pay

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Location & working pattern

Hong Kong, Singapore

- Technical Assessment – Selected candidates will complete a coding challenge focused on core programming and problem-solving skills. - Interviews – Shortlisted candidates will take part in interviews, either on-site or via Microsoft Teams. We’ll explore your technical foundations, how you approach unfamiliar problems and how you work with others. 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.
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