Senior Data Engineer
Senior Data Engineer - Quantitative Trading Firm
Full-Time | Data & Systems Engineering | Permanent Contract
Firm Overview
We are a technology-driven quantitative trading firm operating across multiple asset classes and global financial markets. Our organization places strong emphasis on research, data, and robust engineering, with close collaboration between technologists, researchers, and trading teams. Innovation, performance, and pragmatic problem-solving are central to how we work.
Role Overview
We are seeking a Senior Data Engineer to join our Data Engineering team.
This role plays a key part in shaping and evolving the data platform that supports quantitative research and trading activities. You will work extensively with large-scale financial and time-series datasets, designing systems that make data reliable, accessible, and analysis-ready. Beyond building pipelines, you will help unlock value from data, enabling researchers and traders to move quickly and make informed decisions.
Key Responsibilities
Data Engineering & Platforms
- Data platform design and development: Build and maintain scalable, resilient pipelines for ingesting, processing, and structuring large volumes of financial and market data.
- Time-series and tick data management: Handle high-frequency, high-volume datasets using efficient storage formats and partitioning strategies (e.g., columnar formats).
- Data accessibility: Deliver clean, well-structured, and analysis-ready datasets for quantitative researchers and trading teams.
- Data products and tooling: Develop lightweight dashboards and internal tools to surface data insights for end users.
- Performance and data quality: Optimize data models, queries, and processing workflows to ensure speed, accuracy, and reliability.
Technology Environment
- ETL / ELT orchestration: Python-based workflows, scheduling and orchestration frameworks
- Distributed processing: Large-scale data processing with distributed computing frameworks
- Data storage and analytics: Cloud-based object storage, query engines, and analytics services
- Data formats: Optimized columnar and time-series data formats
Candidate Profile
Required Qualifications
- 5+ years of experience in data engineering or backend software engineering, ideally within finance, trading, or other data-intensive environments
- Strong programming skills in Python, including experience with data processing libraries
- Solid expertise in SQL and distributed data processing frameworks
- Proven experience handling and transforming large-scale, high-frequency time-series data
- Deep understanding of data modeling, query optimization, and performance tuning
- Hands-on experience with cloud-based data platforms and infrastructure
Preferred Qualifications
- Familiarity with financial instruments, trading systems, and market data concepts
- Experience integrating and managing third-party market data sources
- Exposure to DevOps practices and infrastructure-as-code tooling
- Knowledge of parallel and distributed computing techniques
FAQs
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