The Senior Manager, AI & Data Engineering leads teams responsible for building and operating reusable, governed data products and AI-ready semantic intelligence that enable enterprise data integration, activation, analytics, personalization, and decision-making across Vanguard's Participant Financial Success ecosystem. This leader owns the strategy, roadmap, and execution of scalable data, AI, and knowledge platforms that support marketing, sales, digital experiences, strategic analytics, and AI-powered insights. Partnering closely with business, product, analytics, and technology leaders, the role translates data and AI investments into measurable business outcomes while ensuring data quality, governance, security, reliability, and operational excellence. Success in this role requires balancing long-term strategy with hands-on delivery leadership, building organizational capability, and advancing Vanguard's data and AI maturity through modern engineering practices and cloud-native technologies.

This Hybrid Role (in office Tues-Weds-Thurs) is based in Malvern, PA or Charlotte, NC

Responsibilities:

• Lead and develop a high-performing organization of data engineering, AI engineering, and data management professionals, providing coaching, performance management, career development, and succession planning.

• Define and execute the strategy, roadmap, and delivery model for enterprise data products, AI platforms, and knowledge assets aligned to Participant Financial Success business objectives.

• Build and scale reusable, governed data products that enable trusted analytics, reporting, personalization, marketing intelligence, sales enablement, and AI-driven decision-making.

• Establish AI-ready data foundations by advancing semantic intelligence, metadata management, data lineage, knowledge layers, discoverability, and business context across critical data assets.

• Oversee the design, implementation, and operation of scalable cloud-native data platforms, pipelines, services, and lakehouse architectures that support business, analytical, and AI workloads.

• Drive modernization initiatives through AWS-based platforms, automation, DataOps, MLOps, platform engineering, and emerging AI engineering capabilities.

• Partner with senior leaders across Participant Financial Success, Workplace Solutions, Technology, Product, and Analytics to prioritize investments, align delivery plans, and maximize business impact.

• Establish and enforce standards for data governance, quality, privacy, security, observability, compliance, responsible AI, and operational resilience.

• Lead initiatives that break down data silos and create connected data ecosystems, improving accessibility, interoperability, and enterprise-wide data reuse.

• Deliver AI-powered analytics and conversational intelligence capabilities that empower business users to generate trusted insights through natural language interactions.

• Manage platform adoption, reliability, service levels, operational performance, and value realization metrics to ensure solutions deliver measurable outcomes.

• Recruit and develop top talent while fostering a culture of innovation, continuous learning, engineering excellence, and accountability.

• Participate in special projects and perform other duties as assigned.

Qualifications:

• Bachelor's degree or equivalent combination of training and experience required; advanced degree preferred.

• Minimum of ten years of progressive experience in data engineering, data management, analytics, AI/ML engineering, or related technology disciplines.

• Demonstrated experience leading managers and technical leaders within large-scale engineering organizations, including oversight of geographically distributed teams, contractors, and vendor partners.

• Proven success developing and executing enterprise data strategies, modern data platforms, and AI-enabled solutions that deliver measurable business outcomes.

• Deep expertise building cloud-native data ecosystems utilizing AWS technologies such as S3, Glue, EMR, Redshift, Lambda, Athena, and event-driven architectures.

• Experience with enterprise data lakes, lakehouse architectures, governed data products, and large-scale data integration platforms.

• Strong understanding of data governance, metadata management, lineage, data quality, master data, privacy, security, and regulatory compliance practices.

• Experience implementing modern engineering disciplines including DataOps, MLOps, automation, platform engineering, and software delivery best practices.

• Knowledge of AI/ML platforms and technologies, including semantic layers, knowledge systems, conversational analytics, generative AI, and AI-ready data architectures.

• Preferred experience with Databricks, Apache Iceberg, Kafka/Confluent, SageMaker, and modern data observability or governance platforms.

• Strong program leadership, stakeholder management, and executive communication skills with the ability to influence across technical and business functions.

• Demonstrated ability to translate complex technical concepts into strategic business value and actionable outcomes.

Special Factors

Sponsorship

About Vanguard

At Vanguard, we don't just have a mission—we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.