Lead Data Engineer

You'll be at the forefront of building Nike's data foundation and semantic layer - designing and delivering the pipelines, frameworks, and data products that turn raw data into insights shaping product innovation and business strategy. This is hands-on, high-impact work at the intersection of engineering craft and enterprise scale.

• Lead the design, development, and deployment of scalable data pipelines and architectures that power analytics and AI initiatives across CP&I
• Partner with data scientists, analysts, product managers, and business stakeholders to translate requirements into technical specifications and deliver solutions that drive decision-making
• Mentor junior data engineers and champion best practices in coding standards, data governance, and performance optimization
• Build and maintain robust, reusable data engineering components, frameworks, and libraries that process data from diverse sources with consistency and quality
• Monitor, troubleshoot, and optimize data pipelines to ensure high availability, performance, and reliability at enterprise scale
• Implement CI/CD pipelines to automate deployment and testing of data engineering workflows
• Participate in code reviews and contribute to a culture of collaboration, innovation, and continuous improvement

We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form (https://app.smartsheet.com/b/form/5153e46a93f4460db48eb9e611386685) .

We're seeking someone with deep expertise in distributed data processing and cloud-based data platforms who can translate complex business requirements into reliable, production-grade solutions. The ideal candidate brings strong leadership instincts, excels in cross-functional collaboration, and communicates technical concepts clearly to both engineering peers and non-technical stakeholders. Success in this role requires a builder's mindset, a commitment to continuous improvement, and the ability to thrive in a fast-paced environment where data directly fuels innovation and growth.

• Bachelor's degree or equivalent combination of education, experience, or training
• 8+ years of experience as a Data Engineer with strong expertise in Databricks, PySpark, SQL, and Apache Spark
• Hands-on experience with the Databricks Lakehouse Platform, Medallion architecture, Delta Lake, and AWS data services (S3, RDS)
• Proven experience leading and mentoring data engineering teams, with strong skills in CI/CD, Git, and DevOps practices
• Experience with data modeling, ETL/ELT processes, real-time data processing frameworks (Kafka, Kinesis, or similar), and cross-functional stakeholder communication

Preferred qualifications:

• Knowledge of Generative AI and Machine Learning pipelines and integrating them into production environments
• Databricks certification (e.g., Databricks Certified Data Engineer or Databricks Certified Developer for Apache Spark)