Lead Cyber Defense Data Analyst, ITC

This role sits within Nike's Cyber Defence team in Corporate Information Security and is part of the Cyber Incident Response, Analysis and Management team. It works with Privacy, Legal, Incident Response, the Nike Cyber Defence Centre, and leaders and stakeholders across the business. The Lead Cyber Defence Incident Data Analyst supports incident investigations by analysing data impact, solves complex problems using highly technical solutions and playbooks, and drives clarity through analysis and reporting.

• Support incident response investigations by analysing data impact and driving clarity through analysis and reporting.
• Solve complex problems using highly technical solutions and playbooks.
• Build and maintain PySpark pipelines and shared Python libraries for extraction, validation, entity resolution, and analyst-facing views.
• Navigate ambiguous source data, investigate unfamiliar schemas, interpret unclear patterns, and make judgment calls when rules do not cover every case.
• Investigate source data analytically, discover patterns, explain anomalies, and extract insights beyond raw field extraction.
• Build visualisations, dashboards, and in-app methodology guides that make results understandable to non-technical users.
• Operate production jobs on Databricks by deploying, monitoring, triaging failures, and optimising for speed without sacrificing correctness.
• Enforce data quality, traceability, and auditability through hard QC gates, versioned logic, run logs, and documented waivers.
• Use AI coding tools such as Cursor and GitHub Copilot as part of daily workflow while owning review, testing, and what ships.

• Bachelor's degree in computer science or a related field, or equivalent work experience.
• Five years of information technology experience.
• Knowledge of information security standards, principles, and practices.
• Strong project coordination skills, including driving action across multiple stakeholders.
• Experience managing multiple complex workstreams simultaneously.
• Expertise in MS Excel or similar tools to analyse data and extract meaningful insights and trends.
• 4+ years building production data pipelines, with substantial PySpark and Databricks experience (Unity Catalog, jobs, notebooks, volumes).
• Strong Python engineering skills, including modular libraries, pytest, clear abstractions, and comfort debugging distributed Spark jobs.
• Analytical and curious, with the ability to dig into unfamiliar data, form hypotheses, validate them, and explain findings.
• Comfortable working through ambiguity, including incomplete specs, messy inputs, and evolving requirements; able to investigate, make reasoned decisions, and document uncertainty.
• Experience building outputs for non-technical audiences, such as dashboards, reports, or apps that business users can use without reading code.
• Experience with data quality, lineage, and auditability, including grains, traceability keys, idempotent runs, and run logs.
• Comfort in time-bound, high-stakes environments where accuracy matters more than convenience.
• Experience with job orchestration (Databricks Jobs, CI/CD for data assets, failure triage and repair).
• Daily fluency with AI coding tools such as Cursor or GitHub Copilot, using them to move faster while reviewing, testing, and owning the output.

• SIEM and SOAR experience.
• Understanding of Legal Privacy concepts and regulations worldwide.
• One or more of the following professional certifications: CISSP, CBCP, or GIAC.
• Three years of experience in a cyber incident management or business continuity role.