5 months ago
Remote, AmericasSenior
Responsibilities
- Design, build, and maintain production-grade data pipelines and data-intensive systems.
- Configure, schedule, and monitor data pipeline execution for reliable and timely data processing.
- 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 databases.
- Ensure reliable ingestion, transformation, validation, and availability of large-scale and time-series financial data.
- Define and evolve data models and storage structures across relational and NoSQL systems.
- Collaborate with Data Scientists and Analysts to provide accurate and efficient data access for analytics and modeling.
- Optimize workflows, troubleshoot complex data issues, perform root cause analysis, and contribute to the data infrastructure roadmap.
Requirements
- Degree in Computer Science, Engineering, or a related field.
- Strong programming skills in Java, Python, or other JVM-based languages.
- Strong understanding of data modeling, SQL, and NoSQL databases.
- Experience with large-scale and time-series datasets in financial contexts and their data quality challenges.
- Experience building and maintaining production data pipelines or data-intensive systems with a focus on reliability and performance.
- Experience with workflow orchestration and data pipeline scheduling tools.
- Ability to troubleshoot and optimize production data systems.
- Understanding of financial data structures and concepts, including accurately modeling and validating financial data.
- Strong problem-solving skills and attention to detail.
- Professional proficiency in English.
- Experience with monitoring and visualization tools and exposure to machine learning workflows are bonus qualifications.
Benefits
- Competitive salary.
- Truly flexible work environment.
- Unlimited learning and development budget.
- Fast-track career progression with opportunities for technical leadership or principal research roles.
- Collaboration with an international team across offices in Milan, London, and New York.
- Annual company retreat.
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.