Director- Cloud Data Platform

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.

Role purpose

Own the strategy, product roadmap, engineering direction, adoption, reliability and end-to-end service performance of enterprise data and database platforms.

Platform scope

Analytical platforms and services, including Snowflake, Databricks and Microsoft Fabric, together with OLTP and operational database services such as Microsoft SQL Server, PostgreSQL, Oracle and Azure Cosmos DB.

Operating model

Lead platform engineering and product ownership while partnering closely with Operations Service Delivery Managers (SDMs) and support teams for stable, secure and efficient day-to-day service delivery.

Leadership profile

A technically credible platform leader who can translate business demand into product capabilities, influence vendors and stakeholders, and grow adoption across the enterprise.

Position Overview

The Cloud Data Platform Product & Engineering Leader is accountable for the full lifecycle of enterprise data and database platform services. The role combines deep technical leadership with product ownership, service management and commercial influence. It covers analytical and AI-enabled platforms as well as operational and transactional database services, ensuring that the portfolio evolves as a coherent enterprise capability rather than a collection of individually managed technologies.

The leader will define the platform vision and multi-year roadmap, prioritize investment, guide engineering standards, drive adoption, and ensure reliable and secure service delivery. The role will work closely with Operations SDMs, platform engineering teams, architecture, security, risk, application teams, data engineering teams and strategic technology vendors to ensure smooth day-to-day operations while progressing modernization, automation and customer-led product outcomes.

This is not a traditional people-manager or operations-only position. It requires a leader who can move comfortably between executive strategy, architecture and engineering decisions, product prioritization, vendor negotiations, operational governance and direct engagement with internal platform consumers.

Scope boundary: This team will provide Cloud Data Infrastructure Platform Engineering as a product. It will build and operate the shared infrastructure, platform services, automation, controls and self-service capabilities that enable data engineering, analytics, data science and AI/ML teams. It will not perform the application-level data engineering or data scientist activities owned by those consuming teams.

Role Mandate

· Own the enterprise product strategy and roadmap for Cloud Data Infrastructure Platform services supporting analytics, AI/ML, data engineering, OLTP and operational database workloads.

· Run the platform portfolio as a set of secure, resilient, scalable, cost-effective and consumable enterprise products.

· Establish clear service boundaries: the team owns Cloud Data Infrastructure Platform Engineering as a product, while consuming teams retain responsibility for data pipeline development, data transformation, analytical model development, data science and business use-case implementation.

· Balance innovation and modernization with operational stability, regulatory obligations and service performance.

· Increase adoption through clear service offerings, reusable patterns, self-service capabilities, simplified onboarding and an improved developer and customer experience.

· Provide the technical depth and leadership needed to challenge design decisions, guide engineering priorities and build credibility with highly technical teams.

· Create an effective partnership between product and engineering ownership and Operations SDMs responsible for service delivery, support coordination and operational governance.

Key Responsibilities

1. Platform Product Strategy & Roadmap

· Own and communicate the vision, product strategy and multi-year roadmap for the enterprise cloud data and database platform portfolio.

· Define the target Cloud Data Infrastructure Platform portfolio across analytical platforms, AI/ML enablement, OLTP databases, NoSQL services, integration foundations and associated platform capabilities.

· Translate business, application, analytics and engineering demand into prioritized product capabilities, investment proposals and measurable outcomes.

· Manage the full product lifecycle, including capability discovery, business case development, prioritization, delivery, adoption, modernization and retirement.

· Build and maintain a transparent roadmap that balances strategic transformation, regulatory commitments, technical debt, resilience, customer demand and cost optimization.

· Establish product principles, service boundaries, service tiers, consumption models and a clear platform service catalog.

2. Broad Data & Database Platform Ownership

· Own enterprise infrastructure platform direction and service outcomes for Snowflake, Databricks, Microsoft Fabric and other cloud data platform services.

· Own platform direction and service outcomes for OLTP and operational database technologies including Microsoft SQL Server, PostgreSQL, Oracle, Azure Cosmos DB and relevant managed cloud database services.

· Ensure appropriate patterns exist for relational, NoSQL, distributed, streaming and analytical workloads, with clear guidance on technology selection and fit-for-purpose use.

· Drive interoperability across analytical and transactional platforms so that application data, operational data and analytical data can be governed and consumed effectively.

· Partner with architecture and application teams on modernization, database migration, platform consolidation and cloud-native adoption decisions.

3. Technical Leadership & Platform Engineering

· Provide hands-on technical leadership across cloud architecture, database platform engineering, reliability engineering, infrastructure as code, DevSecOps, shared data integration foundations and platform automation.

· Define and govern reference architectures, engineering standards, reusable patterns, deployment approaches, observability requirements and operational readiness criteria.

· Guide the design of secure, scalable, resilient and cost-efficient platform services across Azure and/or AWS environments.

· Challenge designs constructively, lead technical trade-off decisions and ensure engineering investment addresses reliability, maintainability, performance and customer experience.

· Drive automation, policy as code, self-service provisioning, standardized onboarding, automated controls and self-healing capabilities.

· Sponsor technical debt reduction and platform modernization while maintaining service continuity.

4. Adoption, Customer Experience & Internal Client Partnership

· Drive adoption of Cloud Data Infrastructure Platform products by application engineering, data engineering, analytics, data science, AI/ML and business-aligned technology teams.

· Build a structured engagement model with internal clients to understand demand, pain points, onboarding barriers and future capability needs.

· Simplify the customer journey from discovery and architecture consultation through provisioning, onboarding, production readi