The Role:

We are seeking a Senior Data Analyst, for a project based assignment, to deliver high-quality analytics and insights that deepen the organization’s understanding of clients, collections, and commercial performance across boutiques, ecommerce, and wholesale channels. This is a hybrid role combining approximately 60% data analytics and 40% analytics-focused data engineering. You will build analytics-ready datasets and semantic models while leading deep commercial and client analysis, performance storytelling, and structured test-and-learn measurement. Reporting to the Manager, Data & Commercial Analytics, this role serves as a critical bridge between raw enterprise data and business decision-making, ensuring leaders operate with trusted metrics, reliable datasets, and actionable insights.

Key Responsibilities:

• Own client lifecycle and segmentation analysis: who's buying, who's coming back, who quietly stopped, and what that should change about the next collection.
• Analyze assortment, sell-through, and margin down to the boutique level.
• Own the dbt layer: the models behind the boutique, ecommerce, and wholesale data marts, the tests that catch problems before stakeholders do, and the KPI definitions everyone else builds on top of.
• Design and measure test-and-learn programs across campaigns, capsules, and clienteling.
• Build Tableau dashboards for recurring KPI reporting and set up automated distribution through Power Automate.
• Present findings to senior leadership with a recommendation attached, not a dashboard link.
• Chase down data inconsistencies and slow queries as you find them, which you will.
• Field questions from other analysts and help level them up.

Required Qualifications:

• 5+ years in analytics or analytics engineering.
• Advanced SQL.
• Experience in a modern cloud data warehouse. Redshift, Snowflake, BigQuery, Databricks, any of them.
• dbt, or a strong equivalent in another transformation framework.
• Familiarity with retail KPIs: sell-through, full-price ratio, AUR, repeat purchase rate.
• Clear writing. A lot of this work lands in front of executives, and the analysis is only as good as the explanation.
• Discretion with revenue, margin, and client data.

Nice to Have:

• AWS or GCP. Our environment runs on AWS, but you won't need to work in it directly.
• Dagster, Airbyte, or similar orchestration and ingestion tools.
• Python or R.
• Luxury or premium retail background.

Location:

• Must be available to work onsite 3x a week in DTLA

Employment type:

• Contract

*Applicants must be authorized to work for ANY employer in the US. We are unable to sponsor or take over sponsorship of an employment Visa at this time