Lead Software Engineer - Backend, ITC

You will be part of Nike’s Supply Chain and Planning Technology (SCPT) organisation supporting Order Flow Management (OFM) platforms. As a Lead Software Engineer, you will report to an Sr. Engineering Manager/Director and collaborate closely with 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 OFM. This role is critical to building and scaling Nike’s OFM platform - enabling reliable, scalable, and extensible systems that support enterprise-wide capabilities across domains.

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

• 7 - 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)

• Strong backend expertise in Java, Spring Boot, and microservices architecture

• Proven experience designing and operating large-scale distributed systems and REST APIs

• Hands-on experience with event-driven architecture and messaging systems (Kafka, RabbitMQ, or similar)

• Solid experience with cloud platforms (AWS preferred) and cloud-native design principles

• Strong understanding of CI/CD, containerization (Docker/Kubernetes), and DevOps practices

Additional Capabilities (Preferred - Not Mandatory)

• 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

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 operate effectively in a fast-paced, ambiguous environment

As a Lead Software Engineer, you will drive strategy, architecture, and execution for backend systems that power core OFM platform 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 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

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 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