Attribution Search is partnered with a Quantitative Hedge Fund looking to hire a Data Engineer into its Quantitative Platform team.
This is an opportunity to work at the heart of a world‑class quantitative investment business, building the data infrastructure that powers research, alpha generation, and automated trading strategies. You'll be responsible for developing scalable data pipelines, integrating complex financial datasets, and ensuring researchers and trading systems have access to high‑quality, reliable data.
Responsibilities:
- Design, build and maintain production‑grade ETL/ELT pipelines using Python.
- Evaluate, onboard and integrate market, fundamental and alternative datasets from external vendors.
- Build data pipelines that transform raw vendor data into analysis‑ready datasets.
- Develop automated validation and data quality frameworks to ensure accuracy, consistency and reliability across the firm's data platform.
- Support high‑availability data infrastructure, troubleshooting production issues and ensuring uninterrupted data delivery to research and trading teams.
- Work closely with quantitative researchers, developers and technologists to improve data accessibility, performance and scalability.
- Participate in on‑call support and continuously enhance operational resilience across the platform.
Must Have:
- 4+ years' commercial experience building ETL/ELT pipelines using Python.
- Strong experience with modern data engineering technologies such as Kafka, Airflow, S3 and Iceberg.
- Strong understanding of software engineering best practices and operational excellence.
- Excellent communication skills with the ability to work closely with technical stakeholders in a collaborative environment
This is an excellent opportunity for a technically strong data engineer to join a highly collaborative and engineering-focused trading environment with broad exposure across modern data infrastructure and quantitative workflows.
Candidates with relevant experience are encouraged to apply to learn more.
