Artificial Intelligence Data Integration Specialist

About Northern Trust:

Northern Trust, a Fortune 500 company, is a globally recognized, award-winning financial institution that has been in continuous operation since 1889.  

Northern Trust is proud to provide innovative financial services and guidance to the world’s most successful individuals, families, and institutions by remaining true to our enduring principles of service, expertise, and integrity. With more than 130 years of financial experience and over 22,000 partners, we serve the world’s most sophisticated clients using leading technology and exceptional service.

ole Overview 

As a key member of our AI Engineering team, the AI Data Integration Specialist will lead the design and implementation of secure, scalable, and compliant data integration solutions that power AI and machine learning initiatives across the bank. This role is critical to enabling advanced analytics, risk modeling, fraud detection, and intelligent automation in a highly regulated financial environment. 

Key Responsibilities 

• Architect and implement data pipelines that integrate structured and unstructured data from internal banking systems, external feeds, and cloud platforms for AI/ML use cases. 

• Collaborate with data scientists, model risk teams, and business units to understand data requirements for AI models supporting credit risk, AML, KYC, and customer intelligence. 

• Ensure data integration processes comply with regulatory requirements (e.g., BCBS 239, GDPR, CCAR, SR 11-7). 

• Build and maintain metadata management, data lineage, and audit trails for AI data assets. 

• Support real-time and batch data ingestion from core banking systems, trading platforms, and third-party APIs. 

• Optimize data workflows for performance, reliability, and cost-efficiency across hybrid cloud environments. 

• Partner with cybersecurity and compliance teams to ensure data privacy, encryption, and access controls are enforced. 

• Contribute to the development of enterprise-wide AI data architecture standards and governance frameworks. 

Required Qualifications 

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field. 

• 5+ years of experience in data engineering or integration, preferably in financial services or banking. 

• Strong proficiency in Python, SQL, and data integration tools (e.g., Informatica, Talend, Apache NiFi, Airflow). 

• Experience with cloud platforms (Azure, AWS, GCP) and financial data services (e.g., Bloomberg, Refinitiv). 

• Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and model lifecycle management. 

• Deep understanding of data governance, regulatory compliance, and risk management in banking. 

• Excellent communication and stakeholder management skills. 

Preferred Skills 

• Experience with MLOps and model deployment in regulated environments. 

• Knowledge of financial data domains (e.g., credit, market, operational risk). 

• Familiarity with data lakehouse architectures and tools like Databricks, Snowflake, or Delta Lake. 

• Exposure to generative AI and LLM data preparation for financial use cases. 

• Understanding of semantic data integration and financial ontologies.