Data is everywhere these days. Data is generated each time you visit a website or use an app. However, how is this data organized, stored, and used? They can help with that.

A data engineer creates systems for managing, storing, and gathering data. They ensure that data is clear, structured, and prepared for usage by others, including analysts and data scientists. Businesses would find it difficult to use data to make good choices without them.

What they perform, the skills they require, and their significance in the computer industry will all be covered in this post.

What Is Data Engineering?

It means building systems to handle large amounts of data. These systems help businesses collect, clean, and store data so they can use it easily.

Think of it like building roads and pipelines that carry data from one place to another. It makes sure these paths are smooth, safe, and fast.

Their job is to make sure the data is correct, easy to understand, and ready for others to use.

What Does a Data Engineer Do Day to Day?

The daily work can vary depending on the company and the size of the team. But here are some common tasks do every day:

1. Build Data Pipelines

Data pipelines are the tools that move data from one place to another. For example, a pipeline might collect data from a website, clean it, and send it to a database where it can be used for reports. They write code to create these pipelines.

2. Manage Databases

They often set up and maintain databases. They make sure data is stored in a way that is fast and safe. They might also help with choosing the right kind of database for a certain job.

3. Clean and Organize Data

Before data can be used, it often needs to be cleaned. This means fixing errors, removing duplicates, and filling in missing values. They write code to do this automatically.

4. Work with Other Teams

They work closely with data scientists, analysts, and software engineers. They make sure everyone has the data they need in the format they need it.

5. Monitor Data Systems

After data systems are operational, they monitor them. They maintain everything functioning properly by searching for issues, updating, and fixing bugs.

Why Are Data Engineers Important?

Imagine trying to bake a cake without the right ingredients. That’s what it’s like for a data scientist to work without good data. They make sure the "ingredients" are fresh, clean, and ready to use.

In almost every industry, like healthcare, finance, education, and retail, companies depend on data to make decisions. They help to make that data available and useful.

Without data engineers:

Data might be messy or incorrect.
Systems might be slow or crash.
Teams might not be able to get the data they need.

What Skills Are Needed to Be a Data Engineer?

Being a data engineer requires a mix of technical and soft skills.

What Skills Are Needed to Be a Data Engineer

1. Programming Skills

Most of them need to know how to code. Python and SQL are two of the most common languages they use.

Python is used to write scripts for data cleaning and automation.
SQL is used to work with databases.

Some of them also learn other languages like Java or Scala, but Python and SQL are the most important to start with.

2. Understanding of Databases

They work with many types of databases:

Relational databases like MySQL or PostgreSQL.
NoSQL databases like MongoDB.
Cloud databases like Google BigQuery or Amazon Redshift.

They need to know how to design databases and write queries to get data.

3. Knowledge of Data Pipelines and ETL Tools

ETL stands for Extract, Transform, Load. These are the three steps to move data:

Extract data from a source (like a website or app).
Transform the data (clean it, change formats, etc.).
Load the data into a database.

Tools like Apache Airflow, Apache Spark, or Talend help automate these steps.

4. Cloud Platforms

Many companies use cloud platforms like:

Amazon Web Services (AWS)
Google Cloud Platform (GCP)
Microsoft Azure

They often work with cloud tools to store and process large amounts of data.

5. Problem-Solving and Critical Thinking

Things don’t always go as planned. Systems can break, data can be missing, or something might go wrong in the pipeline. They need to be good at solving problems and thinking through solutions.

6. Communication and Teamwork

They don’t work alone. They talk to analysts, scientists, and product teams. Being able to explain technical things in simple ways is a big plus.

How to Become a Data Engineer

If you're thinking about becoming a data engineer, here are some steps you can follow:

1. Learn the Basics

Learn SQL and Python first. Online materials are available for free, and sites like YouTube, Udemy, and Coursera offer basic courses.

2. Understand How Databases Work

Practice writing queries and learn about database design. Set up your own database projects.

3. Build Small Projects

Try building your own data pipelines. You can collect data from public sources (like weather data or sports scores) and create your own reports.

4. Learn Cloud Tools

Pick one cloud platform and get comfortable with it. Google Cloud is great for beginners, and they even offer free credits for practice.

5. Get a Job or Internship

Even if it’s not your dream job, try to get experience working with data. Internships, freelancing, or junior roles can help you grow.

6. Keep Learning

The field of data engineering is always changing. Stay curious and keep learning new tools and best practices.

Common Tools Used by Data Engineers

Here is a list of some popular tools that data engineers use:

Languages: Python, SQL, Scala.
Databases: MySQL, PostgreSQL, MongoDB, BigQuery.
ETL Tools: Apache Airflow, Apache NiFi, Talend.
Cloud Platforms: AWS, GCP, Azure.
Data Warehouses: Snowflake, Redshift, BigQuery.
Other Tools: Docker, Kubernetes, Git, Linux.

Data engineering is a fast growing field with lots of opportunities. As more companies depend on data to make decisions, the need for skilled data engineers continues to rise.

If you enjoy solving problems, working with data, and building systems, this could be a great career for you. It might seem challenging at first, but with time and practice, you can build the skills you need.

Start small, be curious, and keep going. The world of data is big, and there’s always something new to learn.

What Does a Data Engineer Do? | IABAC