Understanding the career path of a data engineer is important before you kick start your new career. The good news is that data engineers have many career path options. We’ve seen people going down different paths and be successful and happy with their jobs.

Senior/Lead/Staff Data Engineer

Data engineers spend most of their time heads down working on implementation, be it a data pipeline or spark job optimization. As the role becomes more senior, the role will get more involved in architectural design meetings and business meetings. Time will also be allocated to mentoring other junior data engineers. A lead data engineer will also be setting the project roadmap along with the leaders and carrying out larger scope data projects. If you want to go down the technical career track and become the staff engineer eventually, be prepared to:

• Go deep and become specialized in certain areas
• Keep learning new technologies in this field and stay abreast with the latest trends
• Work on a variety of large-scale project implementation and widen your knowledge base
• Become a generalist since a large scope project will require more than just one skill
• Get comfortable working with different teams including: software, data science, platform, as well as business.
• Be ready to lead even without a manager title

Manager Track

As the data engineer moves up the career ladder and take up more responsibilities, he/she will start to spend less time on execution and more time on mentoring, business communication, and management. A manager’s role is not the best fit for everyone. Many engineers would avoid becoming a manager so that they can focus on the technology side. However, the persons with the right mindset and motivation will make the transition and thrive in a leadership role.

WCD’s suggestion for those who would like to work in tech leadership roles is that you need to ask yourself the following questions:

• Would enjoy having a job that requires less technical implementation tasks
• Would you enjoy a role that requires you to support other team members instead of focusing on your own growth
• Are you the type who
• Are you dealing with different teams and
• Are you able to have tough conversations and pick up leadership skills

Talking to a mentor who has been in tech leadership roles can be very helpful. Once you’re sure, start preparing early. Opportunities are there for those who are prepared.

Data Science & Analytics

It’s not uncommon to see data engineers going down the data science and analytics route. Data engineers usually work on the data ingestion and ETL parts of the data pipeline but they don’t do a lot of analysis of the data. Since data engineers share a common set of skills such as Python, SQL, AWS, and Spark, it’s not a very big jump from a technical perspective.

However, data engineers will need to put more effort into statistics and machine learning so that they have the advanced analytics skills required for the DS job.

Data Engineering requires less statistics, math, and machine learning. The requirements for coding is higher, data engineers need to be comfortable writing production-grade code. Data transformation functions need to be properly tested. And data engineers also need to have an architect-level view of the entire data pipeline and make sure things run smoothly in production.

Software Engineer

Software engineering can be a good career path for data engineers as well.

Data engineers and web developers share similar skills but the two roles are quite different. For example, a full-stack engineer job will require the knowledge of front-end and back-end development. A data engineer role doesn’t overlap much with it and data engineers will need to learn new skills such as Javascript, React, and/or Node in order to work in web development.

Data engineers have skills more similar to backend software engineers. For example, both need to know RDBMS, NoSQL, Python or Java, APIs, etc. If a data engineer wants to become a software engineer later to work on building data-intensive software application, he/she will need to learn the fundamentals of software development lifecycle and system design.

Tech Evangelist / Developer Advocate

Another interesting path to go down is the tech evangelist route. If you love new technologies, have worked on many different types of projects using different tools and platforms, and love communications and community building, the tech evangelist role might be a good fit. Take the big data world for an example, when new technologies such as Hadoop, Spark got open sourced, many startups were created for that specific technology in the ecosystem. Companies will need very good tech evangelists who come from a technical background and who can help advocate the technologies and build up the developer ecosystem.

Consulting

With so many businesses going through digital transformations, the demand for data consultants become increasingly high. Many companies don’t have the budget to own or experience to run a data engineering and science team. But they still have interesting data problems. Companies that want to collect more data for advanced analytics also want some experts’ help on laying the data infrastructure, migrating legacy systems to the cloud, and building the data pipelines. This is where consultants step in and provide lots of value.

One suggestion WeCloudData would like to give anyone who wants to work on data engineering consulting is that you need to become specialized in certain areas. Companies hiring consultants are usually looking for specific skills. As a consultant, you also need to learn and adapt to new skills very quickly.