Sr Data Analyst

Lennar•Bentonville, AR

3d•Onsite

About The Position

The Sr. Data Analyst on Lennar's Digital Experience Analytics team is an experienced, technically strong professional who transforms complex customer behavioral data into strategic insights that elevate the homebuyer's digital journey. This role operates at the intersection of data engineering, product analytics, and marketing intelligence — partnering closely with product managers, UX designers, and marketing leaders to drive measurable improvements across Lennar.com, CRM, and paid media channels. A career with purpose. A career built on making dreams come true. A career built on building zero defect homes, cost management, and adherence to schedules.

Requirements

Must have advanced SQL skills.
Bachelor’s degree in Computer Science, Information Technology, Business Administration, or a related field. (Master’s degree beneficial).
5–8 years of experience in data analysis, digital analytics, analytics engineering, or a related role; experience in a digital product or e-commerce environment preferred.
Confident with learning new tools, technologies, and methodologies.
Experience with a data transformation tool such as dbt.
Advanced experience with Tableau or similar data visualization tools.
Strong communication, interpersonal, and presentation skills.
Strategic thinker with the ability to see the big picture.

Responsibilities

Own analysis of the end-to-end customer digital journey across Lennar.com and our marketing & sales touchpoints, identifying friction points, and engagement opportunities.
Lead the design, build, testing, and rollout of web behavior tracking, ETL, semantic layer and AI enablement, reporting, and self-serve data tools for product, UX, and marketing stakeholders.
Design, execute, and analyze A/B and multivariate experiments (Optimizely or similar) to optimize digital experiences and drive measurable conversion improvements.
Partner with cross-functional stakeholders to define success metrics, translate complex findings into clear recommendations, and present insights to leadership.
Conduct UAT, provide end-user training, and maintain comprehensive project and analytics documentation.
Leverage AI-enabled tools and emerging methodologies to accelerate analysis and enhance team productivity.