Data engineering is one of today’s most coveted job roles. If you are interested in this job opportunity, you must know what a data engineer career path looks like.

Usually, you can start by getting a degree in computer science. Some professionals also start with little to no experience and knowledge in software development. Knowledge of database management is also relevant and essential in this domain.

Once you start, you can take a data engineer career path to the level of senior data engineer or data architect. As you proceed, you will get to leadership positions and entrepreneurship. This article lists a guideline to help you have a roadmap.

1. Junior Data Engineer 

The first entry-level job opportunity in data engineering is the role of a junior data engineer. These professionals have a computer science bachelor’s degree or similar domains. Most of their responsibilities include data warehousing, software development, etc.

Responsibilities

Here are their roles and responsibilities –

• Junior data engineers usually work under their senior reporting managers.
• In addition, a professional willing to advance in their career must take the necessary certifications and stay updated with emerging technologies.
• These professionals assist their employers with integrating data from different sources. Most importantly, they also run data quality checks.

The junior-level data engineering jobs are under an average pay scale of USD 66,602 per year.

How To Get Started!

• The first step toward this career opportunity requires you to gain a bachelor’s degree in computer science.
• You have to be skilled in data warehousing and programming languages like Python and SQL.
• You can become a certified developer. Or, you can become a Google Cloud Certified Professional Data Engineer.
• Apply for junior data engineer job roles.

This was your first step toward a successful data engineer career path. But what’s next? Well, you level up to the next position.

2. Mid-Level Data Engineers

The mid-level data engineers are a step above the entry-level data engineers. This job role requires one to have a deep comprehension of data warehousing and similar concepts. This professional often has job roles named Senior Data Engineer or Data Warehouse Engineer.

Responsibilities

• The mid-level data engineers work to manage data infrastructure, and they also oversee ETL operations and improve data model architecture. Also, they sometimes collaborate with different data experts—for example, data analysts, data scientists, and the like.
• Sometimes, they also collaborate with other experts in the domain and help support their needs.

Mid-level data engineers usually earn an average salary of 94,313 per annum.

How To Get Started!

• Since it is a mid-level job opportunity in your data science career path, you have to gain a few years of experience first.
• You have to gain more expertise and in-depth knowledge about programming languages, data modeling, and data warehousing.
• You can consider getting a master’s degree in the relevant field.
• Also, get certifications like AWS-certified Big Data.

Mid-level data engineers can advance and get roles like data architects or data scientists. They can continue gaining new skills and certifications and learning about cutting-edge technologies.

3. Senior Data Engineers

When mid-level data engineers have advanced beyond their skills, capabilities, and responsibilities, they mature and become senior data engineers. These professionals thoroughly understand different topics in data engineering.

Some job titles under this particular role include Big Data Architect, Principal Data Engineer, and Lead Data Engineer.

Responsibilities

• Most of these professionals lead a team of data engineers, work on building and implementing complex data structures, and manage big data platforms.
• They work to ensure the scalability, performance, and security of data systems.
• Senior data engineers also work with business stakeholders and data scientists. They work to develop and deploy business solutions.

Your salary will depend a lot on the employer, the location of your employment, and the years of your experience. However, most senior data engineers earn around $158,987 per year.

How To Get Started!

Here are the steps to follow to become a senior data engineer in your data engineering career path.

• First, build in-depth knowledge about big data technologies like Spark and NoSQL databases.
• You also need a bachelor’s degree or master’s degree in computer science, data science, or similar fields.
• You will need to acquire certifications like Cloudera and Certified Data Engineer. Or you can go for AWS Certified Big Data expertise to show your skills in the field.

You can progress from Senior Data Engineer to roles like Data Architect, Chief Data Officer. Some professionals also get promoted to roles l Data Science Manager with experience. However, Ongoing learning is vital for sector advancement.

5. Data science engineer

A data science engineer is responsible for designing, building, and operating a data-driven system.

Responsibilities

• Transition from Senior Data Engineer to Data Architect, Chief Data Officer, or Data Science Manager roles.
• Attain positions through accumulated experience.
• Emphasize continuous learning for industry advancement.

This is one of the high-paying jobs to pursue if you are on a data engineer career path. You can expect to earn around $154,077 per year.

How To Get Started!

• Obtain a bachelor’s or master’s degree in computer science or a related field.
• Gain practical experience in data engineering, data science, or machine learning.
• Consider earning industry certifications like AWS Certified Machine Learning or Google Certified Professional Data Engineer.

These are not the end of what you can do on a journey in a data engineer career. Also, you can work as a data architect, chief data officer, data engineering manager, and more.

Final Words

Data engineering is a rapidly growing field with a promising career outlook. Data engineers can advance along a defined career path, from junior to senior jobs, gaining new skills and responsibilities. What’s more, the growth of data engineering jobs will possibly continue. The reason for that would be more businesses adopting data-centric solutions for creating a strong demand for qualified experts.

So, if you want to advance in a career in data science or data engineering, then it can be a feasible decision for you. However, you must also have a personal interest in a field to start pursuing it as a career option.

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