Lead Software Engineer - Forward Deployed Engineering, ITC

Job description

WHO YOU’LL WORK WITH You 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 FOR

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field 8 - 12 years of experience building scalable backend systems
• 2+ years in a technical leadership role , guiding teams and driving architecture decisions Technical Expertise (Core - Required) Domain expertise in implementing solutions for retail apparel industry specific demand planning, forecasting, and pricing capabilities
• Strong expertise in Full-stack software development and systems architecture
• Proven experience designing and operating large-scale distributed systems including API Design, Integration and Microservices, Database systems and Data Modeling, Security, Compliance and data privacy Hands-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 modelling Understanding of batch and real-time data processing patterns Exposure to frontend technologies such as React or Angular Experience working on enterprise-scale platforms and integrations
• Familiarity with distributed systems and external service integrations
• Solid experience with Cloud infrastructure and deployment patterns (AWS preferred) and cloud-native design principles
• Strong understanding of CI/CD, containerization (Docker/Kubernetes), and DevOps practices

Leadership & Behavioral Skills

• Strong ability to mentor and influence engineering teams
• Proven experience driving technical roadmaps and cross-team alignment
• Excellent 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 environment Bring a strong mindset of Forward Deployment Engineer to implement & deliver at speed and scale WHAT YOU’LL WORK ON As a Lead Software Engineer, you will drive strategy, architecture, and execution for Demand planning and pricing capabilities.

Technical Leadership & Strategy

• Own and drive the technical roadmap for your domain in partnership with Product and Architecture
• Translate complex business requirements into scalable technical solutions
• Lead architectural design decisions and technical reviews across systems

Backend System Design & Development

• Design and build highly scalable backend systems and microservices using Java, Spring Boot, and cloud-native patterns
• Develop robust Data Driven, RESTful APIs and event-driven services for enterprise-scale platforms
• Build resilient distributed systems leveraging messaging platforms like Kafka or similar Data Engineering & Integration (Preferred Strength Area)
• Design and implement data pipelines and integrations across systems and platforms
• Work with modern data platforms (e.g., Spark, Databricks, Delta Lake or equivalent) where required
• Contribute to data quality, consistency, and availability across services Strategize and design Ontology based explainable systems that can drive decisions and insights at high accuracy

Cloud & Platform Engineering

• Lead development and deployment of services on cloud platforms (AWS preferred), ensuring scalability and efficiency
• Drive adoption of CI/CD pipelines, observability, and DevOps best practices

Engineering Excellence

• Establish and enforce high standards in coding, testing, and system reliability Continuously improve system performance and scalability
• Promote modern engineering practices and platform-first thinking

Collaboration & Mentorship

• Mentor engineers across levels and foster a strong engineering culture
• Partner with Business, Product and Engineering leaders to align priorities and execution AI & Engineering Productivity Leverage AI-assisted development tools (e.g., Copilot, code assistants) to improve coding efficiency, testing, and documentation
• Identify opportunities to apply AI/GenAI capabilities to enhance system workflows, automation, and user experiences
• Contribute to establishing best practices for responsible AI usage , ensuring security, data privacy, and reliability Balance AI usage with strong engineering fundamentals, system design, and code quality standards