Apprenticeship – Junior Data Engineer / Data Tools Developer (Quant Research)
About the role
Join our Quantitative Research team as a Junior Data Engineer apprentice (1+ year).
This role is focused on building and improving data tools, pipelines, and workflows used by researchers.
It is not a quantitative research position — we are looking for someone with a strong development mindset who enjoys working on data systems.
You will contribute to making data clean, reliable, and easily usable for quantitative analysis.
Key responsibilities
- Design, build, and maintain data pipelines (ETL/ELT) for financial and market data
- Structure, store and optimize time-series datasets for research usage
- Develop Python and SQL tools for data ingestion, cleaning, and transformation
- Implement automated data quality checks and monitoring processes
- Contribute to internal l data services, APIs, and tooling
- Improve pipeline reliability, performance, and versioning practices
- Work closely with researchers to support their data needs
Required skills
- Good Python skills (Pandas, Numpy)
- Understanding of data pipelines and databases and relational databases
- Ability to write high clean, maintainable and testable code
- Interest in working with structured data
Nice to have
- Experience with SQL (PostgreSQL or equivalent)
- Familiarity with workflow orchestration tools (Airflow, Prefect)
- Exposure to distributed storage (Hadoop, Hive, Spark)
- Knowledge of version control and DevOps practices (Git, CI/CD)
- Interest in financial data
Profile
- Student in engineering school or Master’s (M1/M2) in Computer Science, Data, or related field
- Strong builder mindset: you like creating tools and making systems work
- Curious, autonomous, and detail-oriented
- Interested in a technical role within a quantitative environment (not a researcher role)