Insight Global

Data Analytics Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Analytics Engineer with 7+ years in analytics, advanced SQL skills, and leadership experience. Contract length is unspecified, with a focus on luxury retail analytics. Knowledge of Python or R is a plus. Pay rate is "unknown."
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
480
-
🗓️ - Date
July 1, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Unknown
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Los Angeles, CA
-
🧠 - Skills detailed
#Python #SQL (Structured Query Language) #Automation #BI (Business Intelligence) #Storytelling #Leadership #R #Scala
Role description
Required Skills & Experience - 7+ years of experience in analytics, business intelligence, or data roles, with demonstrated leadership or team-lead exposure. - Advanced proficiency in SQL and modern BI tools, with the ability to design scalable, executive-ready analytics solutions. - Strong commercial acumen, with experience translating data into insights that drive revenue, performance, and decision-making. Nice to Have Skills & Experience - Experience in luxury, premium, or fashion retail environments. - Working knowledge of Python or R for analysis, automation, or advanced analytics use cases. - Experience with client, customer, or consumer analytics across digital or omnichannel touchpoints. Job Description The Data & Commercial Analytics Manager exists to turn this luxury fashion brand's growing volume of retail, e-commerce, wholesale, and client data into clear, trusted commercial decisions. As the brand scales globally, this role ensures leadership teams have a consistent view of performance, client behavior, and opportunities across channels and regions. This is a hands-on leadership role, combining people management with direct analytical ownership. The role defines KPI frameworks, drives performance storytelling, and leads high-impact commercial analysis that informs merchandising, marketing, and clienteling decisions. The role supports the company's transition from ad-hoc reporting to a disciplined analytics operating rhythm, while remaining pragmatic, fast-moving, and closely connected to the business.