Data Engineer LATAM

About MDOTM MDOTM is a global leading provider of AI-driven investment solutions, growing across our offices in London, Milan, and New York. We recently closed a$27M growth equity round, led by Expedition Growth Capital, to support our continued international expansion.

Our proprietary platform, Sphere, currently supports over $100B in assets under management for institutional clients including Morgan Stanley, Amundi, and Zurich Bank.

Role Overview

We are looking for a Data Engineer to play a key role in shaping and scaling our platform as the organization grows in complexity and data maturity. In this role, you will be responsible for designing and evolving the core data infrastructure that powers analytics, machine learning, and critical business decisions.

You will take ownership of how data flows across the company, from ingestion to consumption, ensuring it is reliable, well-modeled, and accessible to a wide range of stakeholders.

Key Responsibilities

Design, build, and maintain production-grade data pipelines and data-intensive systems Configure, schedule, and monitor data pipeline execution to ensure reliability, maintainability, and timely delivery across all data processes Deploy and manage data infrastructure on AWS or on-premises, ensuring scalability, security, and cost-efficiency Monitor and optimize relational and NoSQL database performance (e.

g. , MySQL, PostgreSQL, MongoDB) to ensure efficient querying, indexing, and data access at scale Ensure reliable ingestion, transformation, and availability of large-scale and time-series financial data, considering financial-specific data quality characteristics.

Implement and maintain data quality, validation, and monitoring mechanisms across data workflows Define and evolve data models and storage structures across relational and NoSQL systems Collaborate with Data Scientists and Analysts to ensure accurate and efficient data access for analytics and modeling use cases Optimize data processing workflows for pe