Software Engineer III, ITC

You will report to the Senior Engineering Manager— the enterprise team that curates, governs, and serves Nike Direct and Marketplace data products to BI Experience teams and other GT domains.

You will be a senior individual contributor on the squad, working alongside Leads and Principal engineers to deliver complex backend and data systems.

You will mentor SWE I and SWE II engineers, drive technical design within your squad, and influence patterns and standards that cross-squad teams adopt.

We are looking for senior engineers who own outcomes end-to-end — engineers who can decompose ambiguous problems, drive high-quality designs, and ship complex systems with minimal oversight.

• A minimum of 5–8 years of backend and/or data engineering experience.
• Strong expertise in at least one of Java, Python, or Scala, and confident fluency in SQL and data modeling.
• Proven experience designing and shipping production microservices, RESTful APIs, and event-driven systems.
• Hands-on experience with modern data platforms — Databricks, Spark, Delta Lake, Unity Catalog (or equivalent) — and orchestration tools such as Airflow.
• Solid cloud experience (AWS, GCP, or Azure) including IAM, secrets, networking, and cost-aware design.
• Experience leading non-trivial technical designs, writing design documents, and driving them through review with peers.
• Demonstrated ability to mentor junior engineers — code reviews, pairing, and design coaching.
• Experience with distributed messaging (Kafka, SQS), caching (Redis), and search (Elasticsearch/OpenSearch) where relevant.
• Strong test-driven development discipline, including productive use of AI tools like GitHub Copilot.
• Experience with CI/CD, observability (metrics/tracing/alerting), and incident response.
• Excellent written and verbal communication; able to influence both engineers and senior product/business partners.
• Bachelor's or Master's degree in Computer Science, Information Systems, or related field — or equivalent experience.
• Preferred: experience with data governance, RLS/ABAC, ontology/semantic layers, dbt, agentic/LLM-powered analytics layers, or large-scale BI platforms.