• Build the team + roadmap • Stand up a new platform team (hiring, onboarding, team rituals, execution cadence). • Define a clear, prioritized platform roadmap with measurable adoption outcomes. • Deliver high-leverage platform components • Build “paved roads” that make it easy to ship: reusable patterns, templates, libraries, and reference architectures. • Enable self-service across data + ML workflows with strong governance, security, and observability. • Use a mix of open source and vendor products to build a Data and ML Platform. • Run production-grade operations • Establish quality gates (design reviews, testing strategy, release safety) and platform standards. • Own operational excellence: SLIs/SLOs, on-call readiness, incident response, capacity planning, cost/performance tradeoffs. • Partner across the org • Work closely with Data Engineering, ML Engineering, Analytics, Product, and Security to drive adoption and outcomes.

• Act as a hands-on contributor, designing, developing, maintaining, and scaling Coupa’s platform systems and services • Build reusable microservices, platform components, and frameworks to support standardized data flows (APIs, files, message queues) • Participate in architectural planning, code reviews, and operational design to ensure high-quality, scalable solutions • Promote engineering best practices including unit testing, automation, and clean code principles • Collaborate closely with other teams to simplify deployment, operations, and integration of platform components • Drive continuous improvement by identifying and implementing enhancements to the platform, processes, and overall business

• Analyze large-scale PBM datasets including pharmacy claims, eligibility, formulary, utilization, rebate, and pricing data. • Support executive, clinical, and operational decision-making through data-driven recommendations. • Design, develop, and optimize analytics solutions using Google BigQuery, Cloud Storage, and GCP-native tools. • Build and maintain performant SQL queries, views, and datasets for PBM performance, KPIs, and regulatory reporting. • Ensure data quality, integrity, and compliance across cloud-based data pipelines. • Develop and maintain Power Apps. • Utilize Power Automate to streamline workflows and data refresh processes. • Collaborate on Power Apps solutions to support operational and analytical use cases. • Work closely with operations, finance, clinical teams, compliance, and IT. • Partner with data engineering teams to optimize data ingestion and modeling strategies. • Translate business requirements into technical and analytical solutions. • Present complex analytical findings in clear, actionable formats to non-technical audiences. • Document data definitions, metrics, and business logic to support transparency and audit readiness.

• Supporting the Salesforce Platform Engineering team with day-to-day development and administration work • Delivering enhancements, bug fixes, and configuration aligned to team standards • Handle incoming Salesforce support requests: investigate issues, reproduce bugs, perform root-cause analysis, and implement fixes or escalations as needed. • Partner with senior engineers and admins to triage and resolve incidents impacting Sales, Marketing, Customer Success, and other GTM teams. • Monitor platform health (e.g., error logs, integration failures, performance concerns) and surface risks or recurring issues to the team. • Implement declarative configuration in Salesforce: objects, fields, page layouts, record types, Flows, validation rules, assignment rules, and approval processes. • Develop and maintain custom solutions using Apex, Lightning Web Components (LWC), and APIs, following coding standards and patterns set by the Salesforce Platform Engineering team. • Support feature delivery across Sales Cloud and related clouds (e.g., Service Cloud, Experience Cloud, CPQ) under the direction of senior engineers. • Support integration troubleshooting between Salesforce and other enterprise systems (e.g., ERP, product, customer success platforms) by reviewing logs, payloads, and error messages, escalating complex issues as needed. • Contribute to data quality initiatives, including deduplication, data updates, and enforcing validation and governance standards. • Collaborate with business stakeholders, admins, engineers, and analysts to understand requirements and clarify acceptance criteria. • Maintain documentation for configuration, customizations, integrations, and runbooks to support operational excellence. • Other duties as assigned.