Lead Software Engineer - Forward Deployed Engineering, ITC

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

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

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8 - 12 years of experience building scalable backend systems

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2+ years in a technical leadership role , guiding teams and driving architecture decisions

Technical Expertise (Core - Required)

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Domain expertise in implementing solutions for retail apparel industry specific demand planning, forecasting, and pricing capabilities

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Strong expertise in Full-stack software development and systems architecture

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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

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

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Exposure to data engineering ecosystems (Spark, Databricks, or similar)

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Strong fundamentals in SQL and data modelling

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Understanding of batch and real-time data processing patterns

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Exposure to frontend technologies such as React or Angular

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Experience working on enterprise-scale platforms and integrations

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Familiarity with distributed systems and external service integrations

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Solid experience with Cloud infrastructure and deployment patterns (AWS preferred) and cloud-native design principles

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

Leadership & Behavioral Skills

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Strong ability to mentor and influence engineering teams

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Proven experience driving technical roadmaps and cross-team alignment

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Excellent communication and stakeholder management skills, ability to directly work with the business users.

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Ability to adapt and operate effectively in a continuously changing, fast-paced, ambiguous environment

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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.

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Technical Leadership & Strategy

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Own and drive the technical roadmap for your domain in partnership with Product and Architecture

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Translate complex business requirements into scalable technical solutions

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Lead architectural design decisions and technical reviews across systems

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Backend System Design & Development

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Design and build highly scalable backend systems and microservices using Java, Spring Boot, and cloud-native patterns

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Develop robust Data Driven, RESTful APIs and event-driven services for enterprise-scale platforms

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Build resilient distributed systems leveraging messaging platforms like Kafka or similar

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Data Engineering & Integration (Preferred Strength Area)

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Design and implement data pipelines and integrations across systems and platforms

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Work with modern data platforms (e.g., Spark, Databricks, Delta Lake or equivalent) where required

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Contribute to data quality, consistency, and availability across services

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Strategize and design Ontology based explainable systems that can drive decisions and insights at high accuracy

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Cloud & Platform Engineering

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Lead development and deployment of services on cloud platforms (AWS preferred), ensuring scalability and efficiency

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Drive adoption of CI/CD pipelines, observability, and DevOps best practices

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Engineering Excellence

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Establish and enforce high standards in coding, testing, and system reliability

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Continuously improve system performance and scalability

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Promote modern engineering practices and platform-first thinking

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Collaboration & Mentorship

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Mentor engineers across levels and foster a strong engineering culture

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Partner with Business, Product and Engineering leaders to align priorities and execution

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AI & Engineering Productivity

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Leverage AI-assisted development tools (e.g., Copilot, code assistants) to improve coding efficiency, testing, and documentation

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Identify opportunities to apply AI/GenAI capabilities to enhance system workflows, automation, and user experiences

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Contribute to establishing best practices for responsible AI usage , ensuring security, data privacy, and reliability

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Balance AI usage with strong engineering fundamentals, system design, and code quality standards