Lead Software Engineer

Is a Lead Software Engineer in Marketplace Data Engineering, reporting to the Senior Engineering and serving as the technical leader for a data product squad. The squad covers domains such as Nike Direct, Wholesale Demand, Inventory, 3PP Demand, Customer Dimensional data, WFM, Clickstream, Member, or Orderbook. The engineer will partner with Product Managers, Architects, BI Experience leads, and other engineering leads across Nike to define the strategy and roadmap for consumption and ontology layers, while mentoring junior engineers and raising engineering practices.

• Lead the design of consumption layers, APIs, and pipelines that BI Experience teams build on, establishing patterns, contracts, and quality bars.
• Drive aggressive simplification and unification of the data products landscape, reducing KLO/TCO while improving consistency.
• Co-create agentic and ontology-driven consumption experiences with BI Experience teams, embedding business context and metric consistency into code and systems.
• Own production reliability, scalability, and security for the squad's services, leading incident response, capacity planning, and operational quality.
• Mentor and grow SWE I and SWE II engineers on the squad, raising the technical bar through reviews, pairing, and design coaching.
• Partner with the Platform team to adopt and contribute back recommended toolkits, blueprints, and patterns.
• Represent the team in cross-org architecture forums and influence the broader Nike data architecture.
• Partner closely with Product Managers, Architects, BI Experience leads, and other engineering leads across Nike to define the strategy and roadmap for the squad's consumption and ontology layers.
• Act as the technical leader for the squad, raising the bar on engineering practices and helping to accelerate delivery.

• A minimum of 7–10 years of backend and/or data engineering experience.
• Deep expertise in at least one of Java, Python, or Scala, and strong fluency in SQL and data modelling.
• Proven experience designing distributed systems and data products, including microservices, REST/GraphQL APIs, event-driven architectures, and batch and streaming pipelines.
• Hands-on experience with Databricks, Spark, Delta Lake, Unity Catalog (or equivalent), and orchestration tools such as Airflow.
• Strong cloud experience (AWS, GCP, or Azure) including networking, IAM, secrets, and cost-aware architecture.
• Demonstrated ability to lead technical design reviews, define APIs and data contracts, and drive consensus across teams.
• Track record of mentoring engineers, including code reviews, design coaching, and career growth conversations.
• Experience with observability and SRE practices: metrics, tracing, alerting, error budgets, and on-call leadership.
• Comfortable with TDD, modern CI/CD, and the productive use of AI engineering tools (GitHub Copilot, etc.).
• Strong written and verbal communication, able to influence both engineers and senior business stakeholders.
• Bachelor's or Master's degree in Computer Science, Information Systems, or related field — or equivalent experience.

• Experience with data governance, RLS/ABAC, ontology/semantic layers, dbt, agentic/LLM-powered analytics layers, or large-scale BI platforms.