Job Description

As a Data Engineer, you will play a key role in designing, developing, and maintaining enterprise data platforms that support quantitative research, analytics, and investment workflows.

You will be responsible for creating scalable data pipelines, integrating multiple data sources, and ensuring the availability, accuracy, and reliability of business-critical data. Working closely with data scientists, quantitative researchers, software engineers, and business stakeholders, you will help deliver robust data solutions that enable informed investment decisions.

This position requires a proactive, self-driven professional who enjoys taking ownership, solving technical challenges, and continuously improving modern data engineering practices.

Key Responsibilities

• Design, develop, and maintain scalable data platforms and data engineering solutions.
• Build and optimize data pipelines to process, transform, and deliver high-quality data efficiently.
• Develop and maintain data services that support quantitative research and investment workflows.
• Manage the end-to-end lifecycle of data solutions, from design and implementation through production support.
• Ensure data quality, integrity, consistency, and availability across enterprise systems.
• Work with structured and unstructured datasets using modern database technologies.
• Develop efficient data processing solutions using Python.
• Design and optimize data models within Snowflake and MongoDB environments.
• Monitor, troubleshoot, and continuously improve data platform performance and reliability.
• Collaborate with cross-functional teams to understand business requirements and deliver scalable data solutions.
• Contribute to the continuous evolution of the organization's data architecture and analytics capabilities.
• Document technical designs, data models, and operational procedures.

Required Skills & Experience

• 4+ years of experience as a Data Engineer or in a similar data-focused engineering role.
• Strong programming experience with Python.
• Hands-on experience with Snowflake for cloud data warehousing and analytics.
• Experience working with MongoDB and NoSQL databases.
• Strong understanding of data engineering principles, ETL/ELT processes, and data pipeline development.
• Experience designing scalable, reliable, and high-performance data solutions.
• Knowledge of database optimization, performance tuning, and data modeling.
• Strong analytical and problem-solving skills.
• Ability to manage solutions throughout the entire software and data lifecycle.
• Experience working in Agile and collaborative engineering environments.
• English Level: B2.

Preferred Qualifications

• Experience supporting quantitative research, financial analytics, or investment platforms.
• Familiarity with cloud-based data architectures and modern data ecosystems.
• Experience with workflow orchestration tools and data automation frameworks.
• Knowledge of data governance, data quality, and metadata management practices.
• Experience with CI/CD pipelines for data engineering projects.
• Understanding of distributed data processing and scalable analytics platforms.
• Previous experience in financial services, asset management, or capital markets is an advantage.