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Lithia & Driveway

Is this your company?

Very stressful with horrible upper management makes for a horrible job... and no time off! - Sales Lithia & Driveway Employee Review

1.0
Jan 23, 2011
Recommend
CEO approval
Business Outlook

Pros

An entry level job you can get experience in high pressure sales. Pay is 100% commission. You can make good money in the summer but other then that they promise high wages and tell you each month is going to be a high sales month just to keep you from quitting.

Cons

Crazy 60+ Hour weeks. Makes you want to kill yourself. You are forced to work most holidays. You are promised a day off during the week and you end up being forced to come in. Make you wait 3 months to get benefits. Customers hate you and don't seem to understand its your job to sell them a car. Management makes it extremely difficult to make car deals. They make unrealistic goals on everything and yell at you when you can't reach them. It's always your fault when a customer doesn't want to buy on their first trip to the dealership. You have to pressure people into buying cars and they give you bad survey results afterwords because of it. They treat employees like their expendable. Avoid working here unless you are extremely desperate.

Explore other reviews about Lithia & Driveway

5.0
Jun 6, 2026
Recommend
CEO approval
Business Outlook

Pros

Love what I do. Great team members.

Cons

Very Hot on summer days.

5.0
May 15, 2026
Recommend
CEO approval
Business Outlook

Pros

Strong exposure to real business data from automotive sales, finance, inventory, and customer operations. Opportunity to work on high-impact analytics that directly affect dealership performance and revenue. Large-scale company with many datasets and business units, which is good for learning business intelligence and predictive analytics. Growing digital transformation initiatives can provide opportunities to work with modern analytics tools and automation.

Cons

Legacy systems and fragmented data sources may make data cleaning and integration challenging. Traditional corporate structure can sometimes slow down decision-making or the implementation of data-driven ideas. Work may lean more toward reporting/dashboarding than advanced machine learning, depending on the team. Stakeholders may prioritize quick operational insights over long-term data science experimentation. A high-pressure retail environment can lead to tight deadlines and rapidly changing priorities.

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