Enterprise Data Architect

Overview

East West Bank is seeking a highly experienced Enterprise Data Architect to lead the design, modernization, and governance of the bank's enterprise data architecture strategy and AI-ready data ecosystem.

Responsibilities

• Define and lead the enterprise data architecture strategy, target-state roadmap, and modernization initiatives aligned to business priorities, AI enablement, and regulatory requirements.
• Design and maintain scalable and secured enterprise data architectures enabling analytics, AI/ML, governance, regulatory reporting, and operational intelligence use cases.
• Establish enterprise standards (approach, tooling, workflow) for data modeling, metadata management, lineage, reference architecture, semantic layers, integration patterns, and data lifecycle management.
• Lead architecture design for Azure-native and cloud-based enterprise data platforms including Databricks, Azure Data Lake, Synapse, Microsoft Fabric, Azure Data Factory, and Power BI ecosystems.
• Define reusable integration patterns across traditional ETLs, APIs, streaming platforms, operational systems, cloud platforms, and analytical environments.
• Partner with data governance, cybersecurity, risk, compliance, and legal teams to ensure architecture controls support data quality, privacy, retention, lineage, auditability, and regulatory compliance.
• Drive AI-ready architecture initiatives including lakehouse design, semantic modeling, vectorized data architectures, metadata-driven frameworks, and scalable AI data pipelines.
• Partner with engineering, analytics, and business teams to operationalize scalable data products and enterprise data domains.
• Evaluate and implement modern data architecture tooling including metadata/catalog platforms, observability solutions, orchestration frameworks, and governance technologies.
• Lead enterprise data architecture reviews and governance processes to ensure alignment with approved standards, security controls, and target-state architecture principles.
• Serve as a senior advisor to executive leadership, translating complex architecture concepts into actionable technology and business strategies.
• Perform other duties as assigned.

Qualifications

• 8+ years of progressive experience in enterprise data architecture, large-scale data platform modernization, data engineering, or solution architecture within financial services, fintech, insurance, or other highly regulated industries.
• Strong hands-on experience designing and implementing enterprise data architectures in production environments, not solely strategy or governance roles.
• Deep expertise in enterprise data lifecycle management including data modeling, integration architecture, metadata management, lineage, master/reference data management, retention, and governance.
• Strong experience with Azure-native and modern cloud data ecosystems including Azure Databricks, ADLS Gen2, Synapse, Microsoft Fabric, Azure Data Factory, Spark, and distributed data platforms.
• Strong understanding of AI/ML and advanced analytics architecture requirements including AI-ready data pipelines, semantic modeling, feature engineering support, and scalable analytical data environments.
• Hands-on experience with enterprise data architecture tooling including Erwin, ER/Studio, Collibra, Microsoft Purview, Alation, Visio, Lucidchart, or equivalent platforms.
• Strong understanding of modern architecture patterns including lakehouse architecture, event-driven systems, APIs, data mesh, data fabric, and distributed processing frameworks.
• Practical experience implementing enterprise controls supporting data quality, security, privacy, access governance, auditability, and regulatory compliance.
• Strong understanding of banking regulatory expectations including BCBS 239, SR 11-7, RCSA, CCAR, CECL, AML/BSA, and enterprise risk reporting principles.
• Demonstrated ability to influence senior stakeholders and drive alignment across engineering, analytics, infrastructure, governance, cybersecurity, and business teams.
• Excellent communication and executive presentation skills with the ability to simplify complex technical concepts for non-technical stakeholders.
• Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Architecture, or related technical discipline.
• Highly Preferred: Direct experience building enterprise AI/ML or GenAI-ready data platforms within banking or highly regulated industries.
• Experience designing vectorized data architectures, semantic search platforms, feature stores, or AI-enabled data product ecosystems.
• Hands on experience working with vector database tools such as Pinecone, Pgvector, Qdrant, etc.
• Strong expertise in enterprise metadata, cataloging, governance, and lineage frameworks supporting regulatory transparency and audit readiness.
• Experience leading enterprise-wide cloud data transformation or modernization initiatives at scale.
• Hands-on experience with Kafka, event streaming platforms, API gateways, microservices, and real-time data processing architectures.
• Architecture certifications such as Azure Solutions Architect Expert, Databricks Professional Architect, TOGAF, or equivalent.
• Master’s degree in data science, Computer Science, Engineering, or related quantitative discipline.
• Proven ability to operate as a highly autonomous enterprise architect balancing strategy, governance, and hands-on technical leadership.

Compensation

The base pay range for this position is USD $130,000.00/Yr. - USD $200,000.00/Yr. Exact offers will be determined based on job-related knowledge, skills, experience, and location.