Data Intelligence Engineer

About Northern Trust

As a global leader in innovative wealth management, asset servicing, asset management and banking services, Northern Trust (Nasdaq: NTRS) is proud to guide the world’s most successful individuals, families, corporations and institutions.

Since 1889, we have aligned our efforts with our three guiding Principles That Endure: Service, Expertise, and Integrity. Together, they reflect the three cornerstones of business conduct which we strive to instill in our employees, whom we call partners, and to provide to our clients and the communities we serve worldwide.

With more than 135 years of financial experience and over 24,000 partners, we serve the world’s most sophisticated clients using leading technology and exceptional service.

Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future. Northern Trust will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa) 

Data Intelligence Lead

Position Summary

Data Intelligence is responsible for transforming Wealth Management data into actionable intelligence that improves advisor effectiveness, client service, operational efficiency, and business decision-making.

Working closely with business and technology partners, this role identifies opportunities where data can drive measurable outcomes and develops reusable intelligence capabilities that can be leveraged across analytics, applications, and AI. The successful candidate embraces a data-as-a-product mindset, building scalable, trusted, and well-governed intelligence solutions that deliver long-term value.

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Key Responsibilities

Strategic Partnership

Partner with Wealth Management business and technology stakeholders to identify opportunities where data can improve business outcomes.
Translate business needs into scalable intelligence capabilities.
Develop and maintain a roadmap aligned with organizational priorities.
Promote a reusable, sustainable approach to delivering intelligence.

Intelligence Solutions

Design, build, and evolve intelligence capabilities that support business decision-making, including:

Advisor and client opportunities
Operational insights
Relationship intelligence
Risk indicators
Alerts and event detection
Recommendation services
Predictive and AI-assisted insights
Executive and management dashboards

Example use cases include identifying client engagement opportunities, monitoring significant transactions, highlighting advisor coverage needs, detecting operational trends, and supporting Next Best Conversation recommendations.

Collaboration

Partner with Core Data Products, Platform Engineering, Solution Engineering, Application Engineering, Data Science, and Enterprise Architecture to deliver integrated solutions.
Ensure intelligence capabilities are built on trusted, governed data and can be consumed consistently across reporting, applications, and AI experiences.
Foster collaboration between business and technical teams to maximize adoption and business value.

Continuous Improvement

Champion a data-as-a-product mindset by creating reusable intelligence assets rather than one-time analytical solutions.
Continuously refine intelligence capabilities through user feedback, changing business priorities, and emerging technologies.
Promote best practices for quality, governance, documentation, and operational excellence.

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Technical Experience

Experience designing and delivering modern cloud-based data and intelligence solutions using technologies such as:

Microsoft Azure and cloud-native architectures
Databricks Lakehouse Platform, Delta Lake, and Unity Catalog
GraphQL (Apollo Federation), REST APIs, and API-first integration patterns
Azure Cosmos DB, Redis, Neo4j, and relational databases
Streaming data and modern integration patterns
AI, machine learning, predictive analytics, and recommendation engines
DevOps and CI/CD practices

A strong understanding of modern data architecture, data governance, and scalable intelligence solutions is preferred.

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Qualifications

Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related discipline, or equivalent experience.
Experience leading the delivery of modern data, analytics, or intelligence solutions in a cloud environment.
Strong understanding of data architecture, application integration, and modern engineering practices.
Ability to translate business chall