Full Job Description
Role Description
Lead enterprise data layer engineer for a strategic Front-to-Back transformation program. Define the enterprise canonical data model, integration standards, event schemas, API standards, and connectivity patterns to simplify over 100+ system integrations across Front Office, Risk, Finance, Operations, Treasury, Compliance, and Regulatory Reporting.This role owns the enterprise data layer, data strategy, event taxonomy, and integration governance while ensuring scalable, reusable, and consistent data exchange across the organization.
Role Objectives
Enterprise Data Strategy
• Define enterprise canonical data architecture
• Drive adoption of ISDA CDM and enterprise data standards
• Establish enterprise business glossary and semantic consistency
• Define golden sources and system-of-record strategy
• Standardize data ownership and stewardship
Event-Driven Integration
Design and govern:
• Kafka topic taxonomy
• Event contracts and schemas
• Schema Registry governance
• Event versioning strategy
• Replay and recovery standards
• Dead-letter queue (DLQ) strategy
• Event enrichment and routing
Integration Patterns
Establish reusable patterns for:
• Real-time event streaming
• Synchronous REST APIs
• Asynchronous messaging
• Change Data Capture (CDC)
• Batch integration
• File-based transfers
• Request/Reply messaging
• Publish/Subscribe
• Event Notification
• Command messaging
Canonical Data Model
Lead implementation of:
• Trade events
• Position events
• Market data events
• Reference data
• Counterparty data
• Settlement events
• Cash events
• Collateral events
• Margin events
Qualifications and Skills
Experience
• 15+ years in enterprise architecture, data architecture, or integration engineering
• 10+ years in capital markets or investment banking
• Proven leadership of large-scale transformation programs
• Experience defining enterprise-wide data models and integration standards
• Deep understanding of Front-to-Back trade lifecycles across multiple asset classes
• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related technical discipline
• Master's degree (preferred)
• Industry certifications in cloud, enterprise architecture (e.g., TOGAF), or data architecture are advantageous
Technical Expertise
• Apache Kafka / AWS MSK
• Event-Driven Architecture (EDA)
• Java and Spring Boot
• REST and asynchronous APIs
• AWS cloud services
• Azure Databricks, Delta Lake, and Spark
• Schema Registry (Avro/Protobuf/JSON Schema)
• Change Data Capture
• Kubernetes and container platforms
• Canonical Data Models (especially ISDA CDM)
• API gateways and service mesh
• Data governance, metadata management, and lineage tools
Preferred Domain Expertise
• Multi-asset trading (Rates, FX, Credit, Equities, Fixed Income)
• Trade capture, confirmations, clearing, settlements, collateral, margin, risk, finance, and regulatory reporting
• Knowledge of industry standards such as ISDA CDM, FpML, FIX, and ISO 20022
• Experience implementing enterprise streaming platforms that connect Front Office through Operations and Finance in real time
Additional Requirements
SMBC's employees participate in a Hybrid workforce model that provides employees with an opportunity to work from home, as well as, from an SMBC office. SMBC requires that employees live within a reasonable commuting distance of their office location. Prospective candidates will learn more about their specific hybrid work schedule during their interview process. Hybrid work may not be permitted for certain roles, including, for example, certain FINRA-registered roles for which in-office attendance for the entire workweek is required.
