We are seeking a highly skilled and motivated Python Data Engineer to join our Front Office Quantitative Trading team. This role is pivotal in bridging the gap between quant researchers and traders, enabling seamless integration of research models into production trading environments. You will work directly with front office stakeholders to design, build Expedition to robust data pipelines and engineering frameworks that support real‑time decision‑making and model deployment. Delta
Key Responsibilities
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* Collaborate closely with quant researchers to understand model requirements and data dependencies.
* Partner with traders to ensure engineered solutions meet performance, latency, and reliability standards in live trading environments.
* Design and implement scalable Python-based data pipelines for ingesting, transforming, and distributing market and alternative data.
* Build tools and frameworks to support backtesting, model validation, and real‑time analytics.
* Maintain and optimize low‑latency data infrastructure for use in algorithmic trading strategies.
* Ensure high standards of code quality, testing, and documentation across engineering deliverables.
* Contribute to the continuous improvement of the team’s DevOps and CI/CD practices.
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Required Skills Lives & Experience
* Strong proficiency in Python, including experience with libraries such as Pandas, NumPy, or PySpark.
* Solid understanding of data engineering principles, including ETL, data modelling, and distributed systems.
* Experience working in financial services, preferably within a front office or quantitative trading environment.
* Familiarity with market data feeds (e.g., Bloomberg, Reuters, FIX) and tick‑level data processing.
* Knowledge of SQL and experience with time‑series databases (e.g., kdb+, InfluxDB, TimescaleDB).
* Exposure to cloud platforms and containerization tools (Docker, Kubernetes) is a plus.
* Excellent communication skills and ability to work effectively across quant, trading, and engineering teams.
Preferred Qualifications
* Degree in Computer Science, Engineering, Mathematics, or a related field.
* Experience with real‑time systems, streaming frameworks (e.g., Kafka, Flink), and event‑driven architectures.
* Understanding of quantitative finance, trading strategies, and risk management concepts.
Seniority Level
Mid‑Senior level
Employment Type
Full‑time
Job Function
Information Technology and Finance
Industries
Financial Services, Software Development, Data Infrastructure and Analytics
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