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Nike

Director, Data Engineering, ITC

Posted 4 Days Ago
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Remote
Hiring Remotely in Karnataka, IND
Senior level
Remote
Hiring Remotely in Karnataka, IND
Senior level
The Director of Data Engineering will lead Nike's data initiatives by overseeing the development of data platforms, managing a team of engineers, and collaborating with various teams to enhance data accessibility and trust for decision-making and analytics across product creation.
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WHO WE ARE LOOKING FOR

We are looking for a visionary and value‑driven Director of Data 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 operational decision‑making 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.

WHAT YOU WILL WORK ON

This role will lead, support, and develop Data 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.

You will be responsible for:

  • 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
  • Defining and executing the Data Engineering strategy in support of analytics, intelligence, machine learning, and operational use cases
  • Owning the design and implementation of modern data architectures, including lakehouse platforms, curated data layers, and domain‑oriented data products
  • Ensuring data pipelines 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
  • Collaborating with platform, security, and engineering partners to ensure compliant and scalable solutions
  • 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
WHO YOU WILL WORK WITH

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

WHAT YOU BRING
  • 15+ years of experience in data engineering, data platform development, or analytics engineering
  • 5+ years of experience leading and scaling high‑performing technical teams
  • Proven success designing and operating modern cloud‑based data platforms at enterprise scale
  • Deep knowledge of data architecture patterns, including lakehouse, batch and streaming pipelines, and data modeling
  • Strong understanding of data governance, quality, lineage, and operational best practices
  • Experience enabling analytics and machine learning through robust, well‑designed data foundations
  • Hands‑on experience with modern cloud data technologies (e.g., AWS/Azure, Databricks, Snowflake, Kafka/Kinesis, Airflow, dbt)
  • 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

Top Skills

Airflow
AWS
Azure
Databricks
Dbt
Kafka
Kinesis
Snowflake

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