Lead Software Engineer

The Lead Software Engineer in Marketplace Data Engineering is the technical leader for one of Nike's data product squads, reporting to Senior Engineering. The role partners closely with Product Managers, Architects, BI Experience leads, and other engineering leads to define the strategy and roadmap for consumption and ontology layers. The engineer mentors SWE I and SWE II engineers, raises the bar on engineering practices, and helps the team reduce KLO/TCO while accelerating delivery.

• Own the technical direction of a data product squad serving Nike Direct, Wholesale Demand, Inventory, 3PP Demand, Customer Dimensional data, WFM, Clickstream, Member, or Orderbook.
• 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 directly into code and systems.
• Own production reliability, scalability, and security for the squad's services, leading incident response, capacity planning, and the operational quality of what the squad ships.
• Mentor and grow the 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.

• Senior engineers who lead by example, write excellent code, drive crisp design discussions, and grow the people around them.
• 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 — microservices, REST/GraphQL APIs, event-driven architectures, 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 — code reviews, design coaching, career growth conversations.
• Experience with observability and SRE practices: metrics, tracing, alerting, error budgets, 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.