Lead and grow a software engineering team to design, build, and operate scalable data platforms and AI/LLM-powered services. Drive architecture for SDKs, APIs, and microservices, enforce data governance, observability, and best engineering practices, and partner with product and leadership to shape long-term data and analytics strategy.
Who You’ll Work With
Who We Are Looking For
At Nike, we leverage the transformative power of data and technology to empower
athletes* everywhere. The Data & AI (DAI) team is instrumental in building advanced platforms that are scalable, secure, and intelligent, supporting critical decision-making across the Nike universe and enabling tailored experiences for every member of our global community.
Who We Are Looking For
We are searching for a dynamic and driven engineering manager who excels at nurturing high-performing teams. The successful candidate will thrive in a fast-paced, collaborative setting and possess a strong track record of developing and delivering sophisticated data platforms and innovative services.
Skillset Required- Demonstrated technical leadership with deep knowledge and experience in delivering production grade software at scale. Able to dive deep into code and architecture to provide an informed opinion on benefits/trade-offs of different design choices.
- A minimum of 10 years’ comprehensive experience in software development, demonstrating a deep understanding of distributed systems, cloud-native architectural approaches, and modern data platform technologies.
- Comparable Bachelor’s Degree in computer science, software engineering, or applicable field (master’s degree or Ph.D. preferred).
- At least 3 years of proven leadership experience, successfully managing engineering teams with a focus on recruiting top talent, fostering professional growth, and mentoring team members toward career advancement.
- Demonstrated expertise in deploying solutions on at least one major cloud platform—including AWS, Azure, GCP, or OCI—with the ability to adapt to new environments and technologies as needed.
- Extensive practical experience with state-of-the-art technologies in the AIML space, fluency in open-source technologies and impact of standardized platforms. Ability to make build versus buy decisions for AIML tools and technologies.
- A strong familiarity with agentic workflow and current developments in the AI/LLM application landscape.
- Strong grounding in data pipeline frameworks and architectures, coupled with advanced knowledge of metadata management and the implementation of rigorous data governance controls to ensure integrity, security, and compliance.
- Expertise in architectural design patterns and mastery of foundational computer science principles, supporting the creation of resilient, maintainable software systems.
- A proven ability to conceptualise, develop, and deliver high-impact services that scale effectively to meet the demands of a global enterprise.
- Outstanding communication skills and adept stakeholder management, enabling productive collaboration across diverse teams and effective engagement with senior leadership, partners, and key business units.
- Guide and inspire a dedicated team of software engineers, steering them in designing, building, and maintaining robust and scalable data platforms and services that support enterprise-wide needs.
- Lead efforts to architect and deliver SDKs, APIs, and microservices, ensuring that solutions are tailored to meet the evolving data and analytics demands of the organisation with precision and agility.
- Work in close partnership with product managers, architects, and fellow engineering leaders to collaboratively define the overall technical strategy, set ambitious goals, and shape the long-term roadmap for data and analytics initiatives.
- Install a team culture grounded in continuous improvement, creative problem-solving, and a commitment to engineering excellence, fostering an environment where innovation flourishes.
- Champion and enforce best practices in software engineering, data governance, operational monitoring, and platform observability, ensuring stability, compliance, and quality across all deliverables.
- Align engineering projects and decisions with the broader organisational vision, focusing on transformative priorities such as digital modernisation, cloud cost efficiency, and strong data governance frameworks.
- Development of agentic and AI/LLM powered enterprise applications
- Embrace and embody Nike’s core values (maxims) in your work and interactions with peers, stakeholders, and direct reports. Model clarity and accountability as a leader of Nike. Communicate effectively, build trust and strong relationships across the company, do the right thing.
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Delhi, India's capital city, is a place where tradition and progress co-exist. While Old Delhi is known for its rich history and bustling markets, New Delhi is defined by its modern architecture. It's clear the region places a strong emphasis on preserving its cultural heritage while embracing technological advancements, particularly in artificial intelligence, which plays a central role in shaping the city's tech landscape, fueled by investments in research and development.
