How is Clean Tables used?
Zippia reviewed thousands of resumes to understand how clean tables is used in different jobs. Explore the list of common job responsibilities related to clean tables below:
- Wait on tables clean tables set up for lunch and dinner wash dishes prep side dishes delivery food served drinks
- Bus and clean tables, sweep and mop the floors, loading and unloading the dishwasher, food prep
- Wash dishes, clean tables, help waiters/waitresses, clean bathrooms, and empty trash.
- Helped servers clean tables and made sure guests had a sanitary dining experience.
- Clean tables Wash dishes Change soda machines & alcohol for the bar
- Clean tables, interact with customers and attend to their needs.
Are Clean Tables skills in demand?
Yes, clean tables skills are in demand today. Currently, 461 job openings list clean tables skills as a requirement. The job descriptions that most frequently include clean tables skills are bus person dishwasher, busboy/waiter, and bar attendant.
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What jobs can you get with Clean Tables skills?
You can get a job as a bus person dishwasher, busboy/waiter, and bar attendant with clean tables skills. After analyzing resumes and job postings, we identified these as the most common job titles for candidates with clean tables skills.
Bus Person Dishwasher
- Cleanliness
- Cooking Equipment
- Clean Tables
- Dishwashers
- Clean Kitchen
- Food Preparation Equipment
Bar Attendant
- Cleanliness
- Front Desk
- Quality Standards
- Guest Satisfaction
- Clean Tables
- Cash Handling
Mess Attendant
- Customer Service
- Food Safety
- Facility Residents
- Cooking Equipment
- Clean Tables
- Food Line
How much can you earn with Clean Tables skills?
You can earn up to $28,157 a year with clean tables skills if you become a bus person dishwasher, the highest-paying job that requires clean tables skills. Busboy/waiters can earn the second-highest salary among jobs that use Python, $24,702 a year.
| Job title | Average salary | Hourly rate |
|---|---|---|
| Bus Person Dishwasher | $28,157 | $14 |
| Busboy/Waiter | $24,702 | $12 |
| Bar Attendant | $24,295 | $12 |
| Mess Attendant | $32,416 | $16 |
| Waiter And Cashier | $24,818 | $12 |
Companies using Clean Tables in 2026
The top companies that look for employees with clean tables skills are The Cheesecake Factory, North Italia, and Hy-Vee. In the millions of job postings we reviewed, these companies mention clean tables skills most frequently.
| Rank | Company | % of all skills | Job openings |
|---|---|---|---|
| 1 | The Cheesecake Factory | 25% | 2,906 |
| 2 | North Italia | 16% | 403 |
| 3 | Hy-Vee | 10% | 796 |
| 4 | Buffalo Lodging Associates, Llc | 7% | 188 |
| 5 | Suburban Inns | 5% | 69 |
Departments using Clean Tables
| Department | Average salary |
|---|---|
| Retail | $34,594 |
| Hospitality/Service | $32,016 |
1 courses for Clean Tables skills
1. Cleaning Data In R with Tidyverse and Data.table
Welcome to this course on Data Cleaning in R with Tidyverse, Dplyr, Data. table, Tidyr and many more packages! You may already know this problem: Your data is not properly cleaned before the analysis so the results are corrupted or you can not even perform the analysis. To be brief: you can not escape the initial cleaning part of data science. No matter which data you use or which analysis you want to perform, data cleaning will be a part of the process. Therefore it is a wise decision to invest your time to properly learn how to do this. Now as you can imagine, there are many things that can go wrong in raw data. Therefore a wide array of tools and functions is required to tackle all these issues. As always in data science, R has a solution ready for any scenario that might arise. Outlier detection, missing data imputation, column splits and unions, character manipulations, class conversions and much more - all of this is available in R. And on top of that there are several ways in how you can do all of these things. That means you always have an alternative if you prefer that one. No matter if you like simple tools or complex machine learning algorithms to clean your data, R has it. Now we do understand that it is overwhelming to identify the right R tools and to use them effectively when you just start out. But that is where we will help you. In this course you will see which R tools are the most efficient ones and how you can use them. You will learn about the tidyverse package system - a collection of packages which works together as a team to produce clean data. This system helps you in the whole data cleaning process starting from data import right until the data query process. It is a very popular toolbox which is absolutely worth it. To filter and query datasets you will use tools like data. table, tibble and dplyr. You will learn how to identify outliers and how to replace missing data. We even use machine learning algorithms to do these things. And to make sure that you can use and implement these tools in your daily work there is a data cleaning project at the end of the course. In this project you get an assignment which you can solve on your own, based on the material you learned in the course. So you have plenty of opportunity to test, train and refine your data cleaning skills. As always you get the R scripts as text to copy into your RStudio instance. And on course completion you will get a course certificate from Udemy. R-Tutorials Team...