WHO YOU’LL WORK WITHYou will be part of Nike’s Supply Chain and Planning Technology (SCPT) organization supporting Demand Planning and Pricing (DPP) platforms. As a Lead Software Engineer, you will report to an Sr. Engineering Manager and collaborate closely with Demand and Assortment Planners, Principal Engineers, Product Managers, and cross-functional partners. You will act as the technical leader for your squad, guiding and mentoring engineers while working across teams to deliver scalable platform capabilities across DPP.This role is critical to building and scaling Nike’s Planning platform - enabling reliable, scalable, and extensible systems that support enterprise-wide capabilities across domains.WHO WE ARE LOOKING FOREducation & ExperienceBachelor’s or Master’s degree in Computer Science, Engineering, or related field8 - 12 years of experience building scalable backend systems2+ years in a technical leadership role, guiding teams and driving architecture decisionsTechnical Expertise (Core - Required)Domain expertise in implementing solutions for retail apparel industry specific demand planning, forecasting, and pricing capabilitiesStrong expertise in Full-stack software development and systems architectureProven experience designing and operating large-scale distributed systems including API Design, Integration and Microservices, Database systems and Data Modeling, Security, Compliance and data privacyHands-on experience with event-driven architecture and messaging systems (Kafka, RabbitMQ, or similar) Exposure to data engineering ecosystems (Spark, Databricks, or similar)Strong fundamentals in SQL and data modellingUnderstanding of batch and real-time data processing patternsExposure to frontend technologies such as React or AngularExperience working on enterprise-scale platforms and integrationsFamiliarity with distributed systems and external service integrationsSolid experience with Cloud infrastructure and deployment patterns (AWS preferred) and cloud-native design principlesStrong understanding of CI/CD, containerization (Docker/Kubernetes), and DevOps practicesLeadership & Behavioral SkillsStrong ability to mentor and influence engineering teamsProven experience driving technical roadmaps and cross-team alignmentExcellent communication and stakeholder management skills, ability to directly work with the business users.Ability to adapt and operate effectively in a continuously changing, fast-paced, ambiguous environmentBring a strong mindset of Forward Deployment Engineer to implement & deliver at speed and scaleWHAT YOU’LL WORK ONAs a Lead Software Engineer, you will drive strategy, architecture, and execution for Demand planning and pricing capabilities.Technical Leadership & StrategyOwn and drive the technical roadmap for your domain in partnership with Product and ArchitectureTranslate complex business requirements into scalable technical solutionsLead architectural design decisions and technical reviews across systemsBackend System Design & DevelopmentDesign and build highly scalable backend systems and microservices using Java, Spring Boot, and cloud-native patternsDevelop robust Data Driven, RESTful APIs and event-driven services for enterprise-scale platformsBuild resilient distributed systems leveraging messaging platforms like Kafka or similarData Engineering & Integration (Preferred Strength Area)Design and implement data pipelines and integrations across systems and platformsWork with modern data platforms (e.g., Spark, Databricks, Delta Lake or equivalent) where requiredContribute to data quality, consistency, and availability across servicesStrategize and design Ontology based explainable systems that can drive decisions and insights at high accuracyCloud & Platform EngineeringLead development and deployment of services on cloud platforms (AWS preferred), ensuring scalability and efficiencyDrive adoption of CI/CD pipelines, observability, and DevOps best practicesEngineering ExcellenceEstablish and enforce high standards in coding, testing, and system reliabilityContinuously improve system performance and scalabilityPromote modern engineering practices and platform-first thinkingCollaboration & MentorshipMentor engineers across levels and foster a strong engineering culturePartner with Business, Product and Engineering leaders to align priorities and executionAI & Engineering ProductivityLeverage AI-assisted development tools (e.g., Copilot, code assistants) to improve coding efficiency, testing, and documentationIdentify opportunities to apply AI/GenAI capabilities to enhance system workflows, automation, and user experiencesContribute to establishing best practices for responsible AI usage, ensuring security, data privacy, and reliabilityBalance AI usage with strong engineering fundamentals, system design, and code quality standards