Northern Trust is looking to solve the problem of enabling advanced analytics, risk modeling, fraud detection, and intelligent automation in a highly regulated financial environment by designing and implementing secure, scalable, and compliant data integration solutions that power AI and machine learning initiatives across the bank.
Requirements
- 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.
- 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.
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.
Other
- 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.
- Excellent communication and stakeholder management skills.
- Ability to work in a flexible and collaborative work culture.
- Commitment to working with and providing reasonable accommodations to individuals with disabilities.
