Lead Software Engineer, Workday Finance Integrations
$172,500–$260,100 year
On-siteAtlanta, Georgia, United States or Denver, Colorado, United States
Job Summary
Define and govern end-to-end architecture for Workday Financials, Accounting Center, and enterprise integration platforms, setting engineering standards for quality, security, and scalability. Architect and deliver secure, scalable Workday-MuleSoft integrations across Salesforce, RevRec, Vertex, and banking platforms, driving API-led connectivity best practices and integration reliability. Lead adoption of AI developer tools and automation platforms, embedding AI-assisted practices into the engineering workflow and prototyping agentic AI use cases for finance. Design and operate cloud-native integration infrastructure on AWS and/or GCP, modernizing legacy patterns with event-driven, serverless, and microservices approaches aligned to cloud governance standards. Mentor engineers through architecture and code reviews, foster a culture of continuous learning and experimentation, and collaborate cross-functionally to deliver end-to-end solutions at scale.
Required Qualifications
- 10+ years of enterprise software engineering experience
- 5+ years working in Workday Financials / Accounting Center and integration-heavy environments
- Demonstrated technical leadership in architecture and solution design for large-scale enterprise systems
- Expert-level knowledge of Workday technical frameworks: Business Processes, Security, Accounting Center, Prism Analytics, Core Connectors, EIB, Studio, Workday Extend, Orchestrate, BIRT, and Document Transformation
- Hands-on mastery of the MuleSoft Anypoint Platform — Studio, ESB, API Management, CloudHub
- Solid understanding of integration architecture: SOA, event-driven design, API design principles, REST/SOAP web services, and async messaging patterns
- Practical experience with AI developer productivity tools (Cursor, GitHub Copilot, CodeWhisperer)
- Strong analytical and troubleshooting skills, including log analysis (Splunk or similar)
- Excellent written and verbal communication, with the ability to explain complex designs to both technical and business audiences
- A related technical degree
Desired Qualifications
- Familiarity with CI/CD pipelines, Git, and DevOps practices in large-scale engineering environments
- Experience with Agentforce or LLM/agentic AI tooling in an enterprise context
- Knowledge of SOX compliance, enterprise security, and finance/ERP governance frameworks
- Experience with event-driven architectures using Kafka, Pub/Sub, SQS, or equivalent
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