Junior Quant Data Engineer
About the Role
Join a global macro, quantitative systematic investment firm as a Junior Quant Data Engineer. You'll build and maintain the data infrastructure powering research, backtesting, and live trading—working at the intersection of data engineering and quantitative finance.
Responsibilities
Data Engineering
- Build and maintain end-to-end pipelines for market and alternative data (futures, FX, options, macro series)
- Implement ETL processes: ingestion, validation, transformation, and storage of time series data
- Develop data quality checks, anomaly detection, and reconciliation processes
- Maintain logging, alerting, and monitoring for pipelines and scheduled tasks
Research & Trading Support
- Partner with quants, traders, and PMs to deliver research-ready datasets
- Integrate new data sources into research environments (Python/Matlab) and production systems (Python/.NET/Django)
- Process and validate trade sheets, position files, and PnL data
Production Operations
- Support day-to-day operations: investigate data issues, coordinate fixes, maintain production systems
- Automate workflows using Python, VBA, or scripting
- Contribute to internal libraries and propose improvements to data architecture
Requirements
Technical
- Strong Python skills (pandas, NumPy) for data manipulation and automation
- Solid SQL experience (schema design, query optimization, stored procedures)
- Git and standard development practices (code reviews, testing, CI/CD)
- Solid software engineering fundamentals: design patterns, code organization, debugging, and performance tuning.
- Exposure to any of: Matlab, .NET/C#, VBA, Django
Domain Knowledge
- Understanding of time series data and market data structures
- Basic familiarity with global macro asset classes (futures, FX, rates, commodities)
Education & Experience
- Bachelor's or Master's in CS, Engineering, Mathematics, Statistics, Physics, or related field
- 0–3 years in data engineering, quant tech, or similar role (strong internships considered)
Nice to Have
- Experience with market data vendors (Bloomberg, Refinitiv)
- Familiarity with research data libraries, backtesting datasets, or risk/PnL data flows
- Unit/integration testing experience
- Familiarity with containerization (Docker) and deployment patterns (Kubernetes, ECS, or equivalent)
What We're Looking For
- Strong attention to detail and commitment to data accuracy
- Ownership mentality—treats pipelines as products, not scripts
- Clear communicator who can translate business needs into technical solutions
- Comfortable in a fast-paced environment with tight deadlines
- Genuine curiosity about investing and trading, not just engineering
Pay:
- Base salary
- Annual performance-based bonus
Benefits:
- 401(k) matching
- Health insurance
- Paid time off
Job Type: Full-time
Pay: $100,000.00 - $150,000.00 per year
Benefits:
- 401(k)
- Health insurance
- Paid time off
Work Location: In person