5 months ago
Remote, WorldwideMid Level
Responsibilities
- Design, build, and maintain production-grade data pipelines and data-intensive systems.
- Configure, schedule, and monitor data pipeline execution for reliable and timely delivery.
- Deploy and manage scalable, secure, and cost-efficient data infrastructure on AWS or on-premises.
- Monitor and optimize MySQL, PostgreSQL, MongoDB, and other relational and NoSQL database systems.
- Ingest, transform, validate, and make large-scale and time-series financial data available.
- Implement 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 support analytics and modeling use cases.
- Optimize data processing workflows and troubleshoot complex production data issues.
- Contribute to technical decisions and the data infrastructure roadmap.
Requirements
- Degree in Computer Science, Engineering, or a related field.
- Strong programming skills in Java, Python, or another JVM-based language.
- Strong understanding of data modeling, SQL, and NoSQL databases.
- Experience with data quality, validation, and monitoring practices.
- Experience with large-scale and time-series datasets in financial contexts.
- Experience building and maintaining production data pipelines or data-intensive systems with attention to reliability and performance.
- Ability to troubleshoot and optimize production data systems.
- Experience with workflow orchestration and data pipeline scheduling tools.
- Understanding of financial data structures and concepts, including accurate financial data modeling and validation.
- Strong problem-solving skills and attention to detail.
- Professional proficiency in English.
- Experience with monitoring and visualization tools is preferred.
- Exposure to machine learning workflows and related data requirements is a bonus.
Benefits
- Competitive salary.
- Truly flexible work environment.
- Unlimited learning and development budget.
- Fast-track opportunities into technical leadership or principal research roles.
- Collaboration with an international team across Milan, London, and New York.
- Annual company retreat.
- Fast-track career progression and opportunities to grow into leadership roles.
Tech Stack
Categories
Data Engineering
About MDOTM
MDOTM builds Sphere, an AI-driven investment platform for banks, insurers, pension funds, family offices, and wealth/asset managers, providing forward-looking insights, portfolio construction and rebalancing, and automated reporting powered by analytical and generative AI. It sells enterprise software and AI models to institutional investors, delivered as SaaS with supporting services. Headquartered in London and privately held, MDOTM raised $27M in growth equity and counts Morgan Stanley, Amundi, and Zurich Bank among its clients.