数据工程师
Data Engineer
关于MDOTM
MDOTM 是人工智能驱动投资解决方案的全球领导者。2015年成立，2017年我们成为唯一一家被谷歌选中参加硅谷加速计划的欧洲金融科技初创公司。
从那时起，我们持续增长，在伦敦、米兰和纽约设立了办公室。
如果你正在寻找一个快节奏的环境，并且愿意承担责任，这就是适合你的机会！加入我们！
职位概述
我们正在寻找一名数据工程师，以在组织复杂性和数据成熟度不断提升的过程中，发挥关键作用，塑造和扩展我们的平台。
在此职位中，你将负责设计和演进支撑分析、机器学习和关键业务决策的核心数据基础设施。你将负责管理公司内部的数据流动，从数据采集到使用，确保其可靠、建模良好，并可供广泛的利益相关者访问。
主要职责
- 设计、构建和维护生产级数据管道和数据密集型系统
- 配置、调度和监控数据管道执行，以确保所有数据流程的可靠性、可维护性和及时交付
- 在 AWS 或本地部署和管理数据基础设施，确保可扩展性、安全性和成本效益
- 监控和优化关系型和 NoSQL 数据库性能（例如 MySQL、PostgreSQL、MongoDB），以确保大规模查询、索引和数据访问的效率
- 确保大规模和时间序列金融数据的可靠采集、转换和可用性，考虑金融数据特有的数据质量特征
- 在数据工作流中实现和维护数据质量、验证和监控机制
- 在关系型和 NoSQL 系统中定义和演进数据模型和存储结构
- 与数据科学家和分析师合作，确保分析和建模用例中的准确和高效数据访问
- 优化数据处理工作流，提高性能、可靠性和操作稳定性
- 解决复杂的数据问题并推动根本原因分析
- 参与技术决策，帮助制定数据基础设施的发展路线
所需技能与资格（必须项）
- 计算机科学、工程或相关领域的学位
- 精通 Java 或 Python（或其他 JVM 语言）编程能力
查看英文原文
About MDOTM
MDOTM 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 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 performance, reliability, and operational stability
- Troubleshoot 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 databases
- Strong focus on data quality, validation, and monitoring practices
- Experience working with large-scale and time-series datasets in financial contexts, with an understanding of their structure and common data quality challenges
- Experience building and maintaining production data pipelines or data-intensive systems, with focus on reliability and performance
- Ability to troubleshoot and optimize production data systems
- Experience with workflow orchestration and data pipeline scheduling tools
- Solid understanding of financial data structures and concepts, with the ability to model and validate financial data accurately
- Strong 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 requirements
Why 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 environment
- Benefit 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 roles
- Collaborate daily with an ultra-international team (18+ nationalities) spread across our offices in Milan, London and New York
- Annual company retreat at a stunning location
- Fast-track career progression, with opportunities to grow into leadership roles
Originally posted on Himalayas