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

• 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 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