• Define and maintain performant, scalable data models in the data warehouse, with a focus on reliability, reusability, and documentation • Partner with Platform and Data Engineering to build and monitor scalable data pipelines in production • Serve as a technical authority on data modeling standards, tooling choices, and engineering best practices across the analytics function • Translate ambiguous business needs into clean, well-scoped data products — from one-time analyses to production-grade dashboards • Advocate for and drive adoption of industry best practices • Define the organization's experimentation standards: what constitutes a well-designed study, how results are interpreted, and how findings are documented and shared • Design and execute experiments — hypothesis testing, data analysis, A/B tests, quasi-experiments, and observational studies — in partnership with Operations, Marketing, and Product stakeholders • Evaluate, select, and implement the experimentation stack — prioritizing open-source and low-overhead tooling that can mature with the practice • Bring statistical rigor to ambiguous questions: help teams move from "we want to know if X works" to a study design that can actually answer that question • Communicate findings to non-technical audiences with clarity, including Senior Leadership and external partners

• Responsible for designing, developing and testing software for use in external facing software products. • Work with team lead in designing appropriate UI, architectural, database and instrument controls for company’s software products. • Model behaviors, object hierarchies, and database structure. • Conduct unit testing, verification and debugging of systems and troubleshoot to determine any issues and communicate appropriate solutions. • As required, present and participate in peer reviews of code and designs. • Responsible for the extension of existing systems for new capabilities. • As needed, act as lead for sprints for development of one or more software modules.

• Help develop, drive and execute a long-term vision and strategy for the Corporate Payments cross-cutting and core services. • Collaboratively define and implement a comprehensive architectural roadmap for the EnCompass platform, aligning with business objectives, industry best practices, and other Corporate Payments teams. • Foster a culture of innovation, collaboration, empowerment, and continuous learning within the engineering teams. • Continuously challenge the status quo and implement mechanisms to reduce time-to-market using efficient engineering methods. • Collaborate with other Corporate Payments engineering teams to reuse development practices and components to reduce duplication.

• Design and ship AI agents and copilots for Enterprise Platforms that automate joiner mover leaver flows, access requests, troubleshooting, and governance reviews • Wrap existing runbooks and policies in AI powered workflows across internal tools, automations, and conversational interfaces • Build safe data and integration layers for AI using platform APIs, logs, and internal knowledge content, including retrieval augmented patterns where appropriate • Implement prompts, tools, and orchestration flows with clear guardrails, access controls, approvals, and audit trails so governance is built in • Add evaluation, logging, and monitoring so AI features can be tested, rolled out, and debugged like any other production service • Use AI and event driven patterns to improve lifecycle automation, device baselines, and deprovisioning while staying within security and compliance requirements • Create self service experiences and enablement content so employees and support teams can resolve common IT needs and questions without escalation • Lead Tier 3 incidents in your areas and feed incident learnings back into automations, agents, runbooks, and governance rules • Mentor engineers on AI design, code structure, and evaluation and help shape standards and patterns for AI and automation work inside Enterprise Platforms • Partner with Security, GRC, IT Service Delivery, AI Enablement, and platform owners to select high value AI use cases and land them safely and quickly