Lead Data Engineer

Global Sports Jobs Limited; Beaverton (OR); On-site; USD 140,000 - 175,000; Full time

Job summary

Nike in Beaverton, OR is seeking a Lead Data Engineer within the CP&I Data and Analytics Engineering team to design, build, and maintain scalable data pipelines and analytics solutions that power AI, BI, and advanced analytics.

You will mentor junior engineers, set standards for data governance and performance, and collaborate with data scientists, analysts, product managers, and stakeholders to translate requirements into robust data products across the organization.

Qualifications

• Bachelor's degree in Computer Science or related field (or equivalent).
• 8+ years of Data Engineer experience with Databricks, PySpark, SQL, and Apache Spark.
• Hands-on experience with Databricks Lakehouse, Medallion architecture, Delta Lake, and AWS data services.
• Proven leadership mentoring data engineering teams and strong CI/CD, Git, and DevOps practices.
• Experience with data modeling, ETL/ELT, real-time processing (Kafka/Kinesis), and cross-functional communication.

Responsibilities

• Lead the design, development, and deployment of scalable data pipelines and architectures powering analytics and AI initiatives across CP&I.
• Partner with data scientists, analysts, product managers, and business stakeholders to translate requirements into technical specifications and solutions.
• Mentor junior data engineers and promote best practices in coding, data governance, and performance optimization.
• Build and maintain robust data engineering components, frameworks, and libraries for diverse data sources with quality and consistency.
• Monitor, troubleshoot, and optimise data pipelines for high availability, performance, and reliability at enterprise scale.
• Implement CI/CD pipelines to automate deployment and testing of data workflows.
• Participate in code reviews and foster collaboration, innovation, and continuous improvement.

Skills

Mentoring

Cross-functional collaboration

CI/CD

Git

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks Lakehouse Platform

Delta Lake

AWS S3

Apache Spark

Kinesis

Kafka

PySpark

SQL

Job description

About the Role

This role sits within Nike's Consumer Product and Innovation (CP&I) Data and Analytics Engineering team, which partners with data scientists, engineers, analysts, and product managers to build a cross‑capability data foundation and a semantic layer powering Advanced Analytics, Business Intelligence, and AI solutions. The Lead Data Engineer will design, build, and maintain scalable data pipelines and analytics solutions, driving the development of robust data products. The role also leads technical design and development while mentoring junior engineers and setting standards for data governance, performance, and engineering excellence.

Key Responsibilities

• 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 optimise 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

Required Experience & Qualifications

• Bachelor's degree in Computer Science or related field; any suitable combination of education, experience and training will be accepted
• 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 Skills

• 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)

Workplace

• Beaverton, OR - USA