Job Description

Locations

• India, Karnataka

Skills Required

• Data engineeringintermediate
• Backend service technologiesintermediate
• modern cloud technologiesintermediate

Required Qualifications

• 15+ years of experience in Data engineering and Software development, with a strong foundation in distributed systems, cloud-native architectures, and data platforms (experience, 15 years)
• 5+ years of experience leading and scaling high‑performing technical teams (experience, 5 years)
• Proven success designing and operating modern cloud‑based platforms at enterprise scale (experience)
• Strong understanding of data pipeline frameworks, metadata management, and data governance controls (experience)
• Hands-on knowledge of Backend service technologies (Java, Node.js, Python), along with Microservices architecture experience. (experience)
• Hands‑on experience with modern cloud technologies (e.g., AWS/Azure, Databricks, Snowflake, Kafka/Kinesis, Apache Spark, Apache Airflow, dbt) (experience)
• Experience enabling analytics and AI through robust, well‑designed data foundations (experience)
• Fluent in modern software architectural principles and patterns (e.g., REST, domain-driven design, microservices, etc.) (experience)
• Proven ability to deliver high-impact, scalable services (experience)
• Experience working within large organizations or scaled Agile delivery models (experience)
• Exceptional communication and stakeholder engagement skills (experience)
• Ability to translate complex technical concepts into clear, actionable guidance for diverse audiences (experience)
• Bachelor’s degree in Computer Science, Engineering, or equivalent experience. (experience)
• 15+ years of experience in Data engineering and Software development, with a strong foundation in distributed systems, cloud-native architectures, and data platforms (experience, 15 years)
• 5+ years of experience leading and scaling high‑performing technical teams (experience, 5 years)
• Proven success designing and operating modern cloud‑based platforms at enterprise scale (experience)
• Strong understanding of data pipeline frameworks, metadata management, and data governance controls (experience)
• Hands-on knowledge of Backend service technologies (Java, Node.js, Python), along with Microservices architecture experience. (experience)
• Hands‑on experience with modern cloud technologies (e.g., AWS/Azure, Databricks, Snowflake, Kafka/Kinesis, Apache Spark, Apache Airflow, dbt) (experience)
• Experience enabling analytics and AI through robust, well‑designed data foundations (experience)
• Fluent in modern software architectural principles and patterns (e.g., REST, domain-driven design, microservices, etc.) (experience)
• Proven ability to deliver high-impact, scalable services (experience)
• Experience working within large organizations or scaled Agile delivery models (experience)
• Exceptional communication and stakeholder engagement skills (experience)
• Ability to translate complex technical concepts into clear, actionable guidance for diverse audiences (experience)
• Bachelor’s degree in Computer Science, Engineering, or equivalent experience. (experience)

Responsibilities

• 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.
• 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.
• 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
• 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

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