Data Engineer

Data EngineerMDOTM is the global leader in AI-driven investment solutions. Founded in 2015, we earned significant recognition in 2017 as the only European fintech startup selected by Google for its acceleration program in Silicon Valley. Since then, we have been growing continuously, establishing a strong international presence with offices in London, Milan, and New York.If you are looking for a fast-paced environment and you are willing to take ownership, this is the right opportunity for you! Join us!Role OverviewWe 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 ResponsibilitiesDesign, build, and maintain production-grade data pipelines and data-intensive systemsConfigure, schedule, and monitor data pipeline execution to ensure reliability, maintainability, and timely delivery across all data processesDeploy and manage data infrastructure on AWS or on-premises, ensuring scalability, security, and cost-efficiencyMonitor and optimize relational and NoSQL database performance (e.g., MySQL, PostgreSQL, MongoDB) to ensure efficient querying, indexing, and data access at scaleEnsure 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 workflowsDefine and evolve data models and storage structures across relational and NoSQL systemsCollaborate with Data Scientists and Analysts to ensure accurate and efficient data access for analytics and modeling use casesOptimize data processing workflows for performance, reliability, and operational stabilityTroubleshoot complex data issues and drive root cause analysis.Contribute to technical decision-making and help define the roadmap for data infrastructure.Required Skills & Qualifications (Must-Haves)Degree in Computer Science, Engineering, or a related field.Strong programming skills in Java or Python (or other JVM-based languages)Strong understanding of data modeling, SQL, and NoSQL databasesStrong focus on data quality, validation, and monitoring practicesExperience working with large-scale and time-series datasets in financial contexts, with an understanding of their structure and common data quality challengesExperience building and maintaining production data pipelines or data-intensive systems, with focus on reliability and performanceAbility to troubleshoot and optimize production data systemsExperience with workflow orchestration and data pipeline scheduling toolsSolid understanding of financial data structures and concepts, with the ability to model and validate financial data accuratelyStrong problem-solving skills and attention to detail.Professional proficiency in English.Nice to Have (Bonus Skills)Experience with monitoring and visualization tools (e.g., dashboards)Exposure to machine learning workflows and related data requirementsWhy Join Us?Work at the leading edge of technology, leveraging our decade of experience in proprietary AI to build the next generation of industry-defining tools.Competitive salary & truly flexible work environmentBenefit from an unlimited learning and development budget to stay at the bleeding edge of AI research, alongside a fast-track path into technical leadership or principal research rolesCollaborate daily with an ultra-international team (18+ nationalities) spread across our offices in Milan, London, and New YorkAnnual company retreat at a stunning locationFast-track career progression, with opportunities to grow into leadership roles