Data is becoming increasingly important in the way we do business everywhere, from big digital tech startups to even small town companies.

Data drives our decision making, and it's not just important to have the right data, it's also as important to know how to extract insights from it.

Therefore, we can know for sure that data engineers have a very important role in our current society and they will probably continue to important for the foreseeable future.

Although a career in data engineering can be profitable and fulfilling. It is not an easy job, there are certain skills one must learn to become a skilled data engineer.

Here are some of the top skills a data engineer must know:

Databases

Databases are the most common way that data is stored and accessed. Most databases follow a similar approach to how you access your data, but unfortunately there are many flavors and types of databases and they vary in specific ways, knowing the advantages and drawbacks of each type is a must know for any data engineer.

For example, most relational databases have a schema and all data inserted must fit this schema, you store each class of data in a table and each table can relate to other tables, but sometimes storing data like this doesn't make sense.

Non-relational databases, like CouchDB for example, store data in documents, each record is a document and it contains all the data inside of it.

Now this might sound like a very small difference, but depending on how the data is stored, it can have an effect on various things:

• Data access performance: Some databases are optimized for specific purpose, for example ClickHouse is excellent at gathering event data
• Querying difficulty: Some databases are easier to get insights from than others
• Scalability: Some databases, like PostgreSQL are designed for use at scale in a network, but others, like SQLite are more geared towards embedded or local use

There's no one-size fits all approach to databases, you have to assess your use case and choose one accordingly.

Scripting

When you work with different data sources and formats, it's very important to be able to extract the data you need in the shape that you want.

A great way to do this is using scripts, for example in a language like Python, which we recommend learning, given the amount of libraries and tutorials you'll find online related to data processing.

Another great reason to know how to code your own scripts, is that you can automate things, you write a script once and you can run it many times, this could save you, and your coworkers precious time that you could use on something else.

There's no need to get overwhelmed by trying to become an expert Python programmer, but just knowing the basics, for example learning a library like Pandas will be more than sufficient for most data tasks.

Data Security

Having access and processing data is a huge risk, you have important data in your hands, this data could contain personal information and you must understand how to secure it.

One important aspect is managing access to it, who should be able to access your data? this is something that databases and cloud services allow you to configure, but it is your job to know how to configure them properly so that leaks and theft are less likely.

Conclusion

Becoming a data engineer can be a daunting task but with all the information available online, anyone can do it with the right mindset, start with a course, build some small side projects and you'll become a great data engineer in no time!