Domain Architect - Data , Senior Specialist

Vanguard; Malvern (Chester County); On-site; USD 140,000 - 210,000; Full time

Job summary

Vanguard is seeking an Enterprise Data Architect to define and evolve the company’s AI-ready data strategy and data architecture blueprint. You will drive scalable, secure, governed data platforms across cloud environments to empower analytics and data products.

You’ll collaborate with business and technology leaders to set standards, patterns, and roadmaps, delivering trusted data across divisions and enabling AI and machine learning initiatives.

Qualifications

• Deep expertise designing and implementing Databricks Lakehouse solutions.
• Experience with event-driven architectures and Kafka ecosystems.
• Proven ability to architect large-scale data platforms across lakehouse, data warehouse, streaming, and analytics.
• Experience designing cloud-native data solutions within AWS.

Responsibilities

• Architect large-scale cloud-native enterprise data platforms leveraging technologies such as Databricks, Apache Iceberg, and Confluent Kafka to support analytics, AI, and operational workloads.
• Design scalable data platforms supporting operational intelligence, advanced analytics, machine learning, and AI-driven business capabilities.
• Provides hands-on technical leadership in evaluating, prototyping, and implementing emerging data, AI, and cloud technologies.
• Translates complex business and technology requirements into enterprise architecture standards, reference architectures, and implementation roadmaps.
• Serves as a trusted advisor to business and technology leaders, influencing strategic decisions and shaping the future direction of the enterprise data architecture.

Skills

Databricks Lakehouse

Event-driven architectures

Cloud data platforms

Data modeling

Enterprise architecture

Leadership and collaboration

Tools

Databricks Lakehouse Platform

Kafka / Confluent

AWS

Job description

Join Vanguard’s Enterprise Data Architecture team and help shape the future of our AI-Ready Data Strategy. This critical role will help define and evolve the enterprise data architecture blueprint, ensuring our data ecosystem is scalable, secure, governed, and optimized for AI, analytics, and data product enablement. You’ll collaborate across subdivisions to establish standards, patterns, and frameworks that enable trusted, high-quality data for the enterprise. If you’re passionate about modern data platforms, cloud-native architectures, and driving innovation through data, this is your opportunity to make a lasting impact.

Responsible for defining and evolving end-to-end enterprise data architecture across modern cloud data platforms, including platform strategy, data design, technology evaluation, integration patterns, governance frameworks, and AI-ready data capabilities.

Responsibilities

• Architects large-scale cloud-native enterprise data platforms leveraging technologies such as Databricks, Apache Iceberg, and Confluent Kafka to support analytics, AI, and operational workloads.
• Designs scalable data platforms supporting operational intelligence, advanced analytics, machine learning, and AI-driven business capabilities.
• Provides hands‑on technical leadership in evaluating, prototyping, and implementing emerging data, AI, and cloud technologies.
• Translates complex business and technology requirements into enterprise architecture standards, reference architectures, and implementation roadmaps.
• Serves as a trusted advisor to business and technology leaders, influencing strategic decisions and shaping the future direction of the enterprise data architecture.

Qualifications

• Deep expertise designing and implementing solutions on the Databricks Lakehouse Platform is required.
• Strong experience with event-driven architectures, streaming data platforms, and Kafka-based ecosystems is highly desired.
• Proven track record architecting large-scale data platforms, including lakehouse, data warehouse, streaming, and analytical ecosystems.
• Expertise in conceptual, logical, and physical data modeling using multiple modeling methodologies.
• Experience designing cloud-native data solutions within AWS ecosystems is preferred.