1. Data Management: A data engineer needs to be able to effectively manage large amounts of data. This includes being able to store, organize, and process data efficiently.

3. Data Modeling: A data engineer needs to be able to create accurate data models. This includes understanding how data is structured and how it can be related to other data.

4. Data Mining: A data engineer needs to be able to mine data from various sources. This includes understanding how to extract data from databases, web sites, and other sources.

5. Data Visualization: A data engineer needs to be able to visualize data in order to make it easier to understand. This includes using tools such as charts, graphs, and other visual aids.

6. Data Warehousing: A data engineer needs to be able to design and implement data warehouses. This includes understanding how to store data.

7. ETL Processing: A data engineer needs to be able to extract, transform, and load data. This includes understanding how to use ETL tools and how to design ETL processes.

8. Data Security: A data engineer needs to be able to secure data. This includes understanding how to encrypt data, how to authenticate data, and how to authorization data.

9. Data Quality: A data engineer needs to be able to ensure data quality. This includes understanding how to correct data errors, how to detect data anomalies.

10. Project Management: A data engineer needs to be able to manage data engineering projects. This includes understanding how to create project plans.