Senior Business Data Analyst – Ecommerce

Role Overview
We are seeking a highly analytical and business-oriented Senior Business Data Analyst to partner directly with business stakeholders and enable data-driven decision making across our retail and ecommerce organization. This role is ideal for someone who thrives at the intersection of business and analytics—someone who enjoys solving ambiguous business problems, proactively identifying opportunities, and translating data into actionable insights.
The successful candidate will work closely with business functions such as Merchandising, Growth, Marketing, Category Management, and Operations, leveraging SQL, Python, Snowflake, and modern BI tools to deliver meaningful insights, build intuitive dashboards, and empower business users through self-service analytics.
This is a business-facing analytics role and requires exceptional communication, stakeholder management, and consultative problem-solving skills.
Key Responsibilities
Partner directly with business leaders to understand strategic and operational challenges and translate them into analytical solutions.
Analyze large datasets to answer complex business questions and provide actionable recommendations that influence planning and in-season decisions.
Build, enhance, and maintain executive dashboards and self-service reports using Sigma (or equivalent BI platforms).
Perform ad-hoc analysis to identify trends, business opportunities, risks, and performance drivers.
Coach and enable business users to leverage self-service analytics capabilities effectively.
Present analytical findings to non-technical audiences through clear storytelling and data visualization.
Proactively identify business opportunities and recommend analytical approaches without waiting for formal requirements.
Collaborate with Data Engineering and Technology teams to ensure reliable access to high-quality data while remaining focused on business analytics.
Contribute to establishing analytics best practices and improving data-driven decision-making across the organization.
Develop reusable analytical assets and automate repetitive analyses using Python.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Engineering, Statistics, Mathematics, Business Analytics, or a related discipline.
3+ years of experience in a business-facing analytics role supporting business stakeholders.
Strong expertise in SQL with hands-on experience querying large datasets (Snowflake preferred).
Experience with modern BI and visualization platforms (Sigma preferred; Tableau, Power BI, or Looker acceptable).
Demonstrated experience working directly with non-technical business partners and executive stakeholders.
Excellent analytical and problem-solving skills with the ability to work through ambiguous business problems.
Strong communication and presentation skills with the ability to explain technical findings in business language.
Proven ability to independently translate business challenges into analytical requirements and recommend appropriate analytical approaches.
Preferred Qualifications
Experience in Retail and Ecommerce analytics.
Hands-on experience with Snowflake as a cloud data platform.
Experience enabling Self-Service Analytics for business users.
Exposure to conversational AI or AI-powered analytics tools.
Python skills for data analysis, automation, and AI-assisted analytical workflows (Pandas, NumPy, notebooks, scripting).
Experience supporting multi-brand or multi-geography businesses.
Familiarity with experimentation, merchandising analytics, customer behavior analysis, pricing, inventory, or digital commerce metrics.
Technical Skills
SQL (Advanced)
Snowflake
Sigma Analytics (preferred)
Tableau / Power BI / Looker (acceptable alternatives)
Python (Pandas, Jupyter, data analysis, automation) (Preferred)
Excel (Advanced)
Data visualization and storytelling
Business analytics and KPI development
Success Profile
The ideal candidate is:
A proactive business partner rather than an order-taker.
Comfortable navigating ambiguity and defining analytical approaches independently.
Equally confident in business meetings and technical discussions.
Passionate about helping business teams make better decisions through data.
Curious, collaborative, and driven by business outcomes rather than simply producing reports.

Work arrangement
No