Lead Software Engineer

Overview

Technical lead for a data product squad in Marketplace Data Engineering, owning the direction of consumption and ontology layers and mentoring SWE I and SWE II engineers.

What you'll do

• Lead the strategy and roadmap for consumption and ontology layers with Product Managers, Architects, BI Experience leads, and other engineering leads.
• Lead the design of consumption layers, APIs, and pipelines that BI Experience teams build on, establishing patterns, contracts, and quality bars.
• Drive simplification and unification of the data products landscape to reduce 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, including incident response, capacity planning, and operational quality.
• Mentor and grow SWE I and SWE II engineers through code 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.

What you'll need

• A minimum of 7–10 years of backend and/or data engineering experience.
• Deep expertise in at least one of Java, Python, or Scala.
• Strong fluency in SQL and data modeling.
• 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 through 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.

Nice to have

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