A leading quantitative-driven financial firm is looking for a Data Engineer to join their growing team.
This is a highly impactful role where you will be responsible for building scalable, efficient, and reliable data pipelines that power core trading and research operations.
Key Responsibilities
Data Pipeline Development
- Design, develop, and maintain robust Python-based data ingestion pipelines for market data and internal sources.
- Build and manage a unified RPC-based data access library, compatible across research and trading systems.
- Own the lifecycle of new and existing datasets—acquisition, ingestion, validation, and integration.
Data Quality & Monitoring
- Implement automated validation checks for data consistency, completeness, and accuracy.
- Collaborate with researchers to troubleshoot data anomalies and establish data quality benchmarks.
- Vendor & Data Source Management
- Evaluate and onboard new data vendors (e.g., sentiment, factor models, fundamentals).
- Monitor usage and relevance of existing subscriptions to optimize costs and eliminate inefficiencies.
- Maintain a pipeline of exploratory and potential new data sources.
Collaboration & Documentation
- Partner with quant researchers and software teams to integrate data into models and tools.
- Write comprehensive documentation for datasets, processes, and libraries to enable efficient onboarding and collaboration.
Strategic Impact
- Contribute to the long-term evolution of the firm’s data stack.
- Stay up-to-date with trends in financial data, Python tooling, and infrastructure to bring best practices into the team.
- Assist in developing proprietary data signals and custom indicators (e.g., sentiment scores).