Data Engineer - Trading Technology Infrastructure

Millennium Management, LLC

$175K — $250K *
Finance & Insurance
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Strong understanding of reference data management in the trading domain, especially user and instrument master data.
  • 7+ years of experience in data management, integration, or data platform solutions in production environments.
  • Proficient in Python and/or Java for data engineering tasks.
  • Solid grasp of SQL and NoSQL concepts with an emphasis on data performance and integrity.
  • Strong knowledge of data structures and algorithms related to distributed processing.
  • Excellent communication skills for collaboration with cross-functional teams.
  • Self-motivated and proactive in improving project infrastructure.

Responsibilities

  • Design, develop, and maintain real-time and batch data pipelines for reference data processing.
  • Enhance shared data services for mastering, validation, and enrichment of trading reference data.
  • Collaborate with engineering teams to integrate the platform with trading systems.
  • Deliver high-quality data solutions while following best practices and governance standards.
  • Implement AI-driven solutions for data validation and anomaly detection.
  • Proactively identify improvements across the development lifecycle and platform.
  • Take ownership of assigned tasks and drive them to completion.

Benefits

  • Comprehensive benefits package including health, retirement, and wellness plans.
  • Discretionary performance bonuses based on individual and company performance.
  • Opportunity to work on a critical real-time data platform for a leading trading technology firm.
Full Job Description
Data Engineer - Trading Technology Infrastructure

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.

Key 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.


Required Skills / Experience
  • 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.


Preferred Skills / Experience
  • 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.


Additional Information
This role involves the full data lifecycle, from requirements and design through implementation, testing, and production release. The platform will support new business initiatives and help decommission legacy infrastructure. Strong collaboration skills are essential, as the role requires direct interaction with other technology teams across the Millennium organization. If you are a seasoned Data Engineer with experience in trading infrastructure, reference data, and modern AI-enabled data solutions, we encourage you to apply.

Millennium pays a total compensation package which includes a base salary, discretionary performance bonus, and a comprehensive benefits package. The estimated base salary range for this position is $175,000 to $250,000, which is specific to New York and may change in the future. When finalizing an offer, we take into consideration an individual's experience level and the qualifications they bring to the role to formulate a competitive total compensation package.

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