Senior Data Analyst (Retail)

TL;DR

Senior Data Analyst (Retail/Analytics Engineering): Delivering high-quality analytics and insights to deepen understanding of clients and commercial performance with an accent on client lifecycle, segmentation, and data modeling. Focus on building analytics-ready datasets, developing SQL transformations, and translating complex data into actionable business decisions.

Location: Must be based in Los Angeles and available to work onsite 3x a week in DTLA. Must be authorized to work for any employer in the US (no sponsorship available).

Company

A full-service consulting firm providing high-quality solutions and predictable outcomes for clients ranging from startups to Fortune 50 companies.

What you will do

• Lead client lifecycle, segmentation, and commercial performance analysis across boutiques, ecommerce, and wholesale channels.
• Build and maintain analytics-ready datasets, data marts, and semantic models.
• Develop automated dashboards and KPI reporting frameworks to track campaign and clientele performance.
• Develop SQL transformations and implement rigorous data quality checks to ensure reliability.
• Translate analytical findings into executive-ready narratives and actionable business recommendations.
• Mentor analysts and data power users while acting as a trusted partner for commercial teams.

Requirements

• 5–8 years of experience in analytics or analytics engineering roles.
• Advanced SQL proficiency and experience with modern data warehouse environments.
• Hands-on experience with AWS or GCP environments.
• Expertise in BI tooling and retail KPI frameworks.
• Authorized to work for any employer in the US without sponsorship.
• Strong commercial acumen and ability to deliver polished, concise communication.

Nice to have

• Experience with dbt or similar analytics engineering tools.
• Exposure to Python or R.
• Background in luxury or premium retail environments.