Director Software Engineering, ITC

Nike; India; On-site; INR 6,000,000 - 12,000,000; Full time

Job summary

Nike is seeking a visionary Director of Software Engineering to lead the design, build, and evolution of modern data platforms and pipelines that power analytics, ML, and personalized experiences across product creation. You will drive a data-as-a-product mindset while translating business strategy into resilient platforms at scale.

You will partner with product and engineering leaders to manage priorities, foster a culture of learning, and deliver end-to-end data capabilities across

Qualifications

• 15+ years of experience in Data engineering and Software development.
• 5+ years of experience leading and scaling high-performing technical teams.
• Proven success designing and operating modern cloud-based platforms at enterprise scale.
• Strong understanding of data pipeline frameworks, metadata management, and data governance controls.
• Hands-on knowledge of Backend service technologies (Java, Node.js, Python), with Microservices experience.
• Hands-on experience with AWS/Azure, Databricks, Snowflake, Kafka/Kinesis, Apache Spark, Apache Airflow, dbt.
• Experience enabling analytics and AI through robust, well-designed data foundations.
• Fluent in modern software architectural principles and patterns (REST, DDD, microservices).
• Proven ability to deliver high-impact, scalable services.
• Experience in large organizations or scaled Agile delivery models.
• Exceptional communication and stakeholder engagement skills.

Responsibilities

• Leading, mentoring, and managing a cross-functional team of data engineers building and operating scalable data platforms, pipelines, and services.
• Define and execute the technical roadmap with product managers and engineering leaders.
• Own the design and implementation of lakehouse architectures, curated data layers, APIs, and microservices.
• Ensure solutions are reliable, performant, secure, and observable with strong standards.
• Champion data quality, lineage, governance, and metadata practices for trust and self-service data.
• Partner with Intelligence and Analytics teams to enable advanced analytics and AI/ML.
• Balance near-term delivery with long-term sustainability; manage priorities and tradeoffs.
• Attract and develop engineering talent and foster a learning culture.

Skills

Data engineering

Software development

Distributed systems

Cloud-native architectures

Data platforms

Team leadership

Backend(Java)

Backend(Node.js)

Backend(Python)

Microservices

AWS

Azure

Databricks

Snowflake

Kafka

Kinesis

Spark

Airflow

dbt

Education

Bachelor's degree in Computer Science/Engineering

Job description

WHO YOU WILL WORK WITH

We are looking for a visionary and value‑driven Director of Software Engineering to lead the design, build, and evolution of Nike’s modern data platforms and pipelines in support of digital transformation across merchandising, apparel and footwear product creation. This role will deliver the scalable, reliable, and secure data foundations that power analytics, intelligence, machine learning, and personalized experiences across merchandising, design, and development.

The ideal candidate is an inclusive and empowering technology leader with strong architectural instincts, a passion for data as a product, and a proven ability to translate business strategy into resilient data platforms that deliver value at scale.

WHO WE ARE LOOKING FOR

As a leader in the organization, you will partner closely with engineering and product leaders across Consumer Product & Innovation, Platform Engineering and Enterprise delivery teams. You will work hand‑in‑hand to manage priorities, drive alignment and deliver cohesive, end‑to‑end data capabilities.

Key Qualifications:

• 15+ years of experience in Data engineering and Software development, with a strong foundation in distributed systems, cloud-native architectures, and data platforms

• 5+ years of experience leading and scaling high‑performing technical teams

• Proven success designing and operating modern cloud‑based platforms at enterprise scale

• Strong understanding of data pipeline frameworks, metadata management, and data governance controls

• Hands‑on knowledge of Backend service technologies (Java, Node.js, Python), along with Microservices architecture experience.

• Hands‑on experience with modern cloud technologies (e.g., AWS/Azure, Databricks, Snowflake, Kafka/Kinesis, Apache Spark, Apache Airflow, dbt)

• Experience enabling analytics and AI through robust, well‑designed data foundations

• Fluent in modern software architectural principles and patterns (e.g., REST, domain-driven design, microservices, etc.)

• Proven ability to deliver high-impact, scalable services

• Experience working within large organizations or scaled Agile delivery models

• Exceptional communication and stakeholder engagement skills

• Ability to translate complex technical concepts into clear, actionable guidance for diverse audiences

• Bachelor’s degree in Computer Science, Engineering, or equivalent experience.

WHAT YOU WILL WORK ON

This role will lead, support, and develop Data and Software Engineering team members, manage priorities across complex dependencies, and deliver outcomes across organizational boundaries. You will partner closely with Merchandising and Creation product delivery teams, Busines Intelligence and Analytics delivery teams, and Intelligence teams to ensure data is trusted, accessible, and actionable throughout the product creation lifecycle.

Your responsibilities include:

• Leading, mentoring, and managing a cross‑functional team of data engineers responsible for building and operating scalable data platforms, pipelines, and services aligned to multi‑year roadmaps

• Define and execute the technical roadmap in collaborate with product managers and other engineering leaders

• Owning the design and implementation of modern architectures, including lakehouse platforms, curated data layers, APIs, and microservices that enable seamless integration and interoperability

• Ensuring all solutions are reliable, performant, secure, and observable through strong engineering standards and operational excellence

• Championing data quality, lineage, governance, and metadata practices that enable trust and self‑service consumption

• Partnering with Intelligence and Analytics teams to enable advanced analytics and AI/ML through well‑modeled, production‑ready datasets

• Managing priorities, dependencies, and technical tradeoffs while balancing near‑term delivery with long‑term sustainability

• Attracting, developing, and retaining top engineering talent while fostering a culture of learning, ownership, and continuous improvement