WHO YOU’LL WORK WITH
You will partner with globally distributed teams of engineering, product and program teams to ensure that the ecosystem of services remains loosely coupled, independently scalable, and meets the needs of the business. You will work with your peers to develop key innovation features and report into the Senior Engineering Manager for your capability area.
WHO WE ARE LOOKING FOR
We are looking for an experienced Lead Data Analyst with a strong background in the Business Intelligence and MarTech space. The ideal candidate will be passionate about leading end‑to‑end analytical initiatives, starting from defining complex business problems to generating insights and delivering executive‑ready outputs. This role requires someone who can bridge the gap between technical data expertise and strategic business decision‑making, ensuring that Nike’s marketing technology investments translate into measurable impact.
In this position, you will be responsible for translating complex customer and product data into clear, actionable insights and recommendations for senior leadership. You will work closely with marketing stakeholders to understand their needs, design analytical frameworks, and deliver outputs that influence high‑level decisions. Your ability to synthesize large, multifaceted datasets into compelling narratives will be critical in shaping Nike’s Paid and Owned Media and Business Insights platform. Strong communication skills, a collaborative mindset, and a proven track record of delivering business intelligence solutions in the MarTech domain are essential for success in this role.
8 plus years Analytics & Insights experience in leading end‑to‑end analytical initiatives, from business problem definition through insight generation and business‑ready outputs
Strong experience in data analysis, modelling, and visualization using tools and technologies such as Python, Databricks, SQL, Power BI, etc.
Data visualization fundamentals in marketing analytics, digital analytics, or customer data
Experience in using AI-powered solutions which can enhance data insights, automation, and optimize business processes
Strong experience in collaborating with Product Managers and business stakeholders to gather requirements, define analytics and AI-powered solutions, and ensure alignment with product and project goals
Experience in documenting and improving data pipelines, processes, and data flows, ensuring quality, scalability, and security
Experience with implementing CI/CD and leading teams with DevOps responsibilities of deploying and supporting the software in production
Experience with highly collaborative, multi-discipline development team environments
Solid experience in providing detailed product requirements, user stories, and acceptance criteria for analytics
Excellent verbal and written communication and collaboration skills to effectively connect with both business and technical teams
Familiarity with AI-assisted data engineering and data analysis
Bachelor’s degree in Computer Science or Engineering, Information Systems, or a combination of relevant education, experience, and training
Nice to have experience in BI tools like Tableau, Power BI, etc.
WHAT YOU’LL WORK ON
You will design, define, and analyze critical data KPIs that help business teams make profitable decisions within the Paid Media space. You will rely on your understanding of scalable, highly available, and consistent distributed systems to design world-class solutions.Design & Analysis: Partner with Nike MarTech business stakeholders to understand priorities and roadmaps, validate analytical requirements, and present insights and recommendations with clarity and impact.
Collaborate: Work closely with business stakeholders, product managers, and engineers to understand requirements and technical specifications, and deliver the right KPIs and insights.
Explain designs to teammates for alignment and approval.
Apply advanced analytics techniques, including causal, predictive, and prescriptive analytics, to drive deeper understanding of business levers and inform optimal actions
Contribute to AI-driven analytical workflows by defining quality metrics.
Data Engineering: Work with large-scale datasets.
Participate in design reviews with peers to provide feedback.
Performance Optimization: Identify and fix performance bottlenecks across the data pipelines, ensuring high availability and responsiveness.
CI/CD Integration: Integrate with and maintain continuous integration/continuous
deployment pipelines for seamless software delivery.
Agile Methodologies: Participate in Agile processes, including sprint planning, daily
stand-ups, code reviews, and retrospectives.
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.