What Do Data Engineers Need To Know?

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According to the 2020 LinkedIn U.S. Emerging Jobs Report Data engineering jobs are in the top 15 outstanding emerging jobs and have a hiring growth rate that has increased substantially. When it comes to being a Data engineer there are several skills that are needed. Data Engineers are typically a kind of software engineer with their focus being on data and the technology that allows data to be persisted and aggregated.

What Do Data Engineers Do

Data engineers are the ones responsible for laying the foundations for the acquisition, storage, transformation, and management of data in an organisation. They are the specialists that prepare large datasets that are used by analysts. The data engineers also create programs and routines to prepare the data in a layout that an analyst needs to interpret information.

As a result, the data engineer’s day-to-day runs fundamentally between two processes:

• ETL (Extract, Transform, Load) Processes include developing data extraction, transformation, and loading tasks, and moving data between different environments.
• Data Cleaning Processes so that it arrives in a normalised and structured fashion into the hands of analysts and data scientists.

Skills Needed To Be A Data Engineers

1. Database systems (SQL/NoSQL): Data engineers need to know how to manipulate database management systems (DBMS), which is a software application that provides an interface to databases for information storage and retrieval. Whether it be SQL or NoSQL databases (such as a graph or document).
2. Data warehousing solutions: Data warehouses store huge volumes of current and historical data for query and analysis which can come from multiple sources. Cloud services platforms like Amazon Web Services (AWS) provide different data warehousing solutions that data engineers are expected to be familiar with.
3. ETL tools: ETL (Extract, Transfer, Load) refers to how data is taken (extracted) from a source, converted (transformed) into a format that can be analysed and stored (loaded) into a data warehouse. This process uses batch processing to help users analyse data relevant to a specific business problem.
4. Machine learning: Machine learning algorithms — also called models — help data scientists make predictions based on current and historical data. Data engineers only need a basic knowledge of machine learning as it enables them to understand a data scientist’s needs better (and, by extension, the organisation’s needs), get models into production and build more accurate data pipelines.
5. Data APIs: An API is an interface used by software applications to access data. It allows two applications or machines to communicate with each other for a specified task. Data engineers build APIs in databases to enable data scientists and business intelligence analysts to query the data.
6. Python, Java, and Scala programming languages: Programming is one of the most fundamental skill that is needed by data engineers.
7. Understanding the basics of distributed systems: Understanding the core principles of distributed systems are important for data engineering. Such as Hadoop fluency and Apache Spark.
8. Knowledge of algorithms and data structures: Data engineers focus mostly on data filtering and data optimization, but a basic knowledge of algorithms is also helpful to understand the big picture of the organisation’s overall data function, as well as defining checkpoints and end goals for the business problem at hand.

4 Essential Programs Data Engineers Use

Data engineers use the following five essential programs:

• Apache Hadoop and Apache Spark.
• Amazon Web Services/Redshift (for data warehousing).
• Azure.
• HDFS and Amazon S3.

Soft Skills for Data Engineers

Data engineers don’t just need to have hard technical skills they also need soft skills such as:

• Communication skills. On a typical day, data engineers interface with machine learning engineers, data analysts, CTOs, and developers, and so being able to communicate is an important skill to have.
• Collaboration. When teams depend on each other for deliverables, they need to have a healthy give-and-take relationship to keep projects running smoothly and this is the same for data engineers.
• Presentation skills. Depending on the size of the data science team, data engineers may be expected to perform data analysis and present their findings to stakeholders.

If you want to know more about Data engineering you can follow the Eden AI South Africa social media page. If you want to grow more as a Data engineer then you can use our bootcamp to further develop, you can find more information about it @ [email protected]. If you need Data engineers to help your business further develop contact us @[email protected].