Manager, Quality Engineering (Financial Tech & AI Automation)

Lennar•Atlanta, GA

18h•Onsite

About The Position

Lennar’s Finance Product & Engineering team powers the financial backbone of one of America’s largest homebuilders, operating mission-critical platforms within the FP&A, Accounting and Treasury functions including Oracle JD Edwards EnterpriseOne (E1), Hyperion EPM, and Oracle Narrative Reporting. As we accelerate our digital transformation, we need a Quality Engineering & Assurance Manager who can establish robust testing standards, champion automation-first thinking, and build a scalable QE function fit for the AI era. This role is ideal for a practitioner-manager: someone skilled at writing test plans and reviewing automation scripts while also mentoring engineers, shaping QE strategy, and experimenting with AI-powered testing agents to multiply team capacity.

Requirements

7+ years of quality engineering / QA experience in ERP or enterprise finance systems environments
3+ years of experience with Oracle JD Edwards EnterpriseOne (E1) — functional or technical QA in finance modules (GL, AP, AR, FA, Job Cost)
2+ years of hands-on experience with Hyperion EPM products (Planning, Financial Management, or Narrative Reporting)
Demonstrated experience designing and implementing automated test frameworks (Selenium, Tosca, UFT, Playwright, or similar)
Strong understanding of financial close processes, ERP integrations, and reporting data flows
Experience leading or mentoring QE team members; comfort owning team outcomes end-to-end
Proficiency with defect management and test management tools (Jira, Zephyr, qTest, ALM, or equivalent)
Solid grasp of SDLC methodologies — Agile/Scrum, SAFe, or hybrid delivery models

Nice To Haves

Experience with Oracle E1 Orchestrator, Business Services, or BSSV integrations
Familiarity with Hyperion FDMEE / Data Management and DRM for data governance testing
Exposure to AI-assisted testing tools or large language model (LLM) integrations in QE workflows
Experience building QE functions at a greenfield stage — defining process, tooling, and team from scratch
Background in financial services, homebuilding, mortgage, or title industries
Knowledge of SOX IT General Controls (ITGCs) and automated controls testing
ISTQB, CSTE, or equivalent QA certification
Scripting skills in Python, Groovy, or JavaScript for test automation and API testing

Responsibilities

Design, write, and maintain comprehensive test plans, test cases, and test scripts for Oracle E1, Hyperion, and Narrative Reporting workflows including GL, AP, AR, fixed assets, budgeting, and close cycles
Build and own automated regression suites using tools such as Selenium, Tosca, UFT, or equivalent; integrate with CI/CD pipelines
Execute functional, integration, regression, performance, and UAT testing across Finance ERP environments
Perform end-to-end validation of data flows between Oracle E1, Hyperion FDMEE/DRM, and Narrative Reporting
Define and enforce data quality checks, reconciliation controls, and financial reporting accuracy benchmarks
Lead root-cause analysis on defects; partner with developers and functional analysts to drive timely resolution
Create and maintain QE documentation including test strategies, defect tracking standards, metrics dashboards, and release sign-off checklists
Build a QE team from the ground up — recruit, onboard, and develop QE engineers and SDET talent
Define roles, career paths, and competency frameworks for the QE function
Coach team members through code reviews, test case reviews, and QE best practices
Create a culture of quality ownership across the broader engineering and functional teams — quality is everyone’s responsibility
Manage team capacity, sprint commitments, and delivery roadmaps aligned to project milestones
Evaluate, pilot, and implement AI-powered testing agents and frameworks (e.g., LLM-assisted test generation, self-healing tests, intelligent defect triage)
Develop a strategy for human-AI hybrid QE delivery — identifying which test domains are best served by human judgment vs. AI automation
Stay current on emerging QE tools and AI developments; present findings and recommendations to engineering leadership
Explore agentic workflows for continuous monitoring of financial data integrity and automated anomaly detection in reporting outputs
Establish and socialize QE standards, testing gates, and definition-of-done criteria across the SDLC
Partner with Finance functional leads, project managers, and business analysts to clarify acceptance criteria and testing priorities
Manage defect lifecycle end-to-end in tools such as Jira; maintain clear traceability from requirements to test coverage
Report QE metrics — test coverage, defect escape rate, automation ROI, cycle time — to engineering and finance leadership
Support compliance and audit readiness by ensuring test evidence is captured and retained per SOX/internal controls requirements
Coordinate with Oracle support, third-party vendors, and implementation partners on environment and testing dependencies