Quantitative Data Engineer

Quberesearchandtechnologies; Greater London; On-site; GBP 70,000 - 100,000; Full time

Job summary

Qube Research & Technologies (QRT) is seeking a data engineer to join a global quantitative team in London. You will collaborate with Quant Researchers and Traders to design, extract, clean and onboard data for systematic strategies and discretionary trading decisions.

You will manage data ingestion from various sources, ensure data quality, and implement robust extraction processes in a fast-paced, high-performance environment. This role focuses on reliable datasets for research and trading.

Qualifications

• Advanced Python development experience with data-focused libraries.
• Experience with financial datasets and data onboarding processes.
• Strong emphasis on data quality and correctness across datasets.

Responsibilities

• Collaborate with Quant Researchers and Traders to design datasets for systematic strategies and discretionary trading decisions.
• Extract, clean and aggregate data from diverse raw sources using the data framework.
• Own onboarding of new datasets from assessment to production.
• Investigate data issues to speed up dataset availability for users.
• Develop robust data extraction processes with focus on correctness and data quality.
• Explore and implement new data extraction approaches to handle complex datasets.

Skills

Python

Pandas

Polars

NumPy

SQL

Data quality

Communication

High-performance environment

Tools

Pandas

Polars

NumPy

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.

You will work within a data function responsible for making complex financial datasets accessible and reliable for research and trading. You will collaborate directly with Quantitative Researchers and Traders to understand data requirements, onboard new sources and build datasets that support systematic strategies and discretionary trading decisions.

Your future role within QRT

• Collaborate with Quantitative Researchers and Traders to design datasets that support systematic strategies and discretionary trading decisions
• Extract, clean and aggregate data from a wide range of raw sources and formats using QRT’s data framework
• Manage the full process of onboarding new datasets, from initial assessment through to production
• Investigate and resolve data issues to reduce the time required to make new datasets available to users
• Develop robust data extraction processes with a strong focus on correctness and data quality
• Explore and implement new approaches to data extraction that improve the tools available for onboarding complex datasets

Your present skillset

• 3+ years of experience in Data Engineering or a similar role working with financial data
• Advanced Python development skills, including experience with libraries such as Pandas, Polars and NumPy
• Strong focus on correctness, with the ability to critically assess code and data quality regardless of source
• Experience working with SQL and relational databases
• Experience working with both traditional and alternative financial datasets
• Demonstrated interest in financial markets and the application of data to investment research and trading
• Experience within quantitative finance is beneficial
• Excellent communication skills with the ability to collaborate with Quantitative Researchers, Traders, Engineers, management and external data providers
• Ability to operate effectively in a high performance environment with rapid delivery cycles

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.