Data Engineer - Trading Technology Infrastructure

Millennium•New York, NY

1d•Onsite

About The Position

The Trading Technology Infrastructure team at Millennium is responsible for providing shared services to internal trading systems. We are seeking a Data Engineer to join our global development team in the buildout of our strategic real-time data platform. This platform is critical for ingesting, storing, enriching, and distributing high-quality reference data from multiple sources in real time to support the development of a global order management system and other core trading services. This role has a strong focus on reference data engineering and the application of AI-driven techniques to improve data quality, automation, monitoring, and operational efficiency.

Requirements

Trading Domain Knowledge: Strong understanding of reference data management within the trading domain, especially user, instrument, and destination master data.
Data Engineering Experience: 7+ years of professional experience building data management, integration, or data platform solutions in production environments.
Programming: Strong hands-on development skills in Python and/or Java.
Database Knowledge: Proficient in database concepts across SQL and NoSQL technologies, with a focus on data integrity, scalability, and performance.
Data Structures & Algorithms: Strong understanding of data structures and algorithms relevant to distributed data processing and reference data systems.
Communication Skills: Strong communication skills for effective interaction with team members and stakeholders across technology teams.
Ownership Mindset: Self-starter and critical thinker who takes ownership of projects and proactively suggests infrastructure and platform improvements.
Continuous Delivery: Experience building and supporting systems using continuous integration and continuous deployment practices.

Nice To Haves

Experience with real-time data platforms and event-driven architectures.
Familiarity with AI/ML techniques for data quality monitoring, intelligent matching, anomaly detection, or workflow automation.
Experience with PostgreSQL or other relational databases for data storage and retrieval.
Familiarity with GraphQL for efficient data access and integration.
Experience with AWS for cloud-based data solutions.
Background in trading infrastructure, order management systems, or front-office data platforms.

Responsibilities

Design, develop, and maintain scalable real-time and batch data pipelines for reference data ingestion, processing, and distribution.
Build and enhance shared data services that support mastering, validation, enrichment, and delivery of critical trading reference data.
Work closely with engineering teams and stakeholders to ensure seamless platform integration across trading systems.
Deliver high-quality data solutions with quick turnaround times while adhering to best practices, governance standards, and production controls.
Apply AI-enabled approaches to improve data validation, anomaly detection, metadata management, and support automation.
Take ownership of tasks and proactively identify opportunities to improve the overall platform, development lifecycle, and infrastructure.