Career Development

15 Data Quality Engineer Skills for Your Career and Resume

Learn about the most important Data Quality Engineer skills, how you can utilize them in the workplace, and what to list on your resume.

Data quality engineers are responsible for ensuring that data is accurate, consistent and reliable. They use a variety of skills to perform their duties, including data analysis, data cleansing and data mining. If you’re interested in a career as a data quality engineer, understanding these skills can help you determine if this job is a good fit for you.

Data Warehousing

Data quality engineers use data warehousing skills to store and organize large amounts of data. They may also create a database that allows other employees to access the information they need quickly. Data warehousing involves creating tables, columns and rows in a relational database management system (RDBMS) so that all the data is organized by subject. This can help ensure that the data is accurate and easy for others to find when needed.

Data Analysis

Data analysis is the process of examining data to find trends and patterns. Data quality engineers use this skill when reviewing data to determine if it’s accurate, complete or consistent with company standards. They also analyze data to identify areas where they can improve their processes to ensure that incoming data meets these standards.


ETL, or extract-transform-load, is a process that data quality engineers use to clean and organize large amounts of data. Data quality engineers typically need to know how to perform these processes in order to do their job effectively. They may also be responsible for training other employees on the proper way to use ETL software.

Data Governance

Data governance is the process of managing data throughout its lifecycle. Data quality engineers use this skill to ensure that all data in an organization is accurate and consistent. They also use it to determine which data needs to be deleted, archived or updated. This ensures that the company has access to the most up-to-date information.

Critical Thinking

Critical thinking is the ability to analyze a situation and find solutions. Data quality engineers use critical thinking skills when they review data for accuracy, consistency and integrity. They also use these skills when creating new processes or procedures to ensure that their methods are effective and efficient.


Organization is the ability to keep track of your work and materials. Data quality engineers often have many projects at once, so it’s important for them to be able to organize their time and resources effectively. This skill also helps them maintain a clean workspace that makes it easier to find files when they need them.

Organization can also help data quality engineers stay on task during meetings or presentations. They may need to take detailed notes or record information about new processes, so being organized can make it easier for them to remember details later.

Problem Solving Skills

Problem solving skills are necessary for data quality engineers to identify and resolve issues in their work. They may use these skills when reviewing data, analyzing the source of errors or anomalies and developing solutions to fix them. Data quality engineers also use problem-solving skills when troubleshooting computer systems, software programs and other technology they use on the job.

Attention to Detail

Data quality engineers must be able to identify and correct errors in data sets. This requires attention to detail, as you may need to examine large amounts of information to find the source of an error. You also use your attention to detail when creating new data models or updating existing ones. For example, if a company changes its name from “Company A” to “Company B,” you may need to update all instances of the old name with the new one.

Data Migration

Data quality engineers need to have knowledge of data migration, which is the process of moving data from one system to another. Data quality engineers use this skill when they work with software developers who create new applications and programs that replace older ones. They also use it when they help companies upgrade their computer systems or change cloud storage providers.

Master Data Management

Master data management is the ability to manage large amounts of data and ensure it’s accurate. Data quality engineers often use master data management skills when they create new databases or update existing ones. They may also need these skills to ensure that their own personal information, such as addresses and phone numbers, is correct.

Data Modeling

Data modeling is the process of creating a model for data storage. Data models are used to ensure that data can be retrieved and stored in an organized manner. Data quality engineers use data modeling when creating new systems or updating existing ones. This skill allows them to create efficient data storage methods that allow others to find information quickly.


SQL is a programming language used to create and manage databases. Data quality engineers use SQL when creating data models, which are diagrams that show how data should be stored in a database. They also use SQL to query the database, which means they ask it questions about its contents. This can help them identify any issues with the database’s structure or content.


Communication skills are necessary for data quality engineers to convey their ideas and instructions to other team members. Data quality engineers also use communication skills when they communicate with clients about the status of projects or potential issues that arise during a project. Strong written and verbal communication skills can help data quality engineers explain technical concepts to non-technical audiences, which is often necessary in this field.

Business Intelligence

Business intelligence is the ability to analyze data and interpret its meaning. Data quality engineers use business intelligence when they review incoming data for accuracy, consistency and completeness. They also use it when they create reports that summarize their findings or make suggestions for improvement.

Data Cleansing

Data cleansing is the process of removing and correcting errors in data. Data quality engineers use this skill to ensure that the data they provide to clients is accurate and free of mistakes. For example, if a client requests information about their sales by region, the data quality engineer ensures that the data provided has no inconsistencies or missing values.

How Can I Learn These Data Quality Engineer Skills?

There are a few ways that you can learn the skills necessary to become a Data Quality Engineer. One way is to take courses offered by companies or organizations that specialize in data quality management. These courses will teach you the basics of data quality, including how to identify and correct errors, how to develop and implement quality control procedures, and how to monitor data quality.

Another way to learn the necessary skills is to work with a company or organization that already has a data quality management system in place. This will allow you to see firsthand how the system works and to learn from the people who are already experienced in data quality management. You can also learn from books and articles that are written on the subject.


16 Human Factors Engineer Skills for Your Career and Resume

Back to Career Development

16 Instrumentation Engineer Skills for Your Career and Resume