Data Engineer
Role Overview
We are seeking a proactive and highly skilled Data Engineer to design, build, and maintain the robust data infrastructure that powers our analytics and business decision-making. In this hands-on role, you will take ownership of the end-to-end data lifecycle - from architecting pipelines to active production support, ensuring our quantitative and analytical teams have uninterrupted access to high-quality, scalable datasets.
Core Responsibilities:
- Pipeline Engineering: Architect, build, and maintain scalable, automated data workflows and pipelines that ingest large-scale datasets from external vendors, exchanges, and internal systems.
- Data Management & Quality: Implement rigorous validation pipelines to clean, organize, and verify incoming data, ensuring absolute accuracy, consistency, and reliability for downstream users.
- Analytics Enablement: Partner directly with analysts, researchers, and trading desks to translate complex business requirements into high-performing data solutions and interactive dashboards.
- Production Support & Monitoring: Actively monitor system alerts, logs, and platform health. Troubleshoot missing, delayed, or incorrect data, providing rapid first-line support to ensure uninterrupted business operations.
- Architecture & Governance: Contribute to the continuous evolution of the firm’s data architecture while enforcing security, compliance, and lifecycle management best practices.
Experience & Qualifications:
- 5–7 years of professional experience in data engineering or software engineering, preferably within a fast-paced or financial services environment.
- Proven track record taking full ownership of technical solutions, from initial design and testing through CI/CD deployment and post-launch support.
- Exceptional analytical and problem-solving skills, with the ability to rapidly identify and resolve operational bottlenecks in large datasets.
- Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field.