The Data Engineer Career Guide
Data engineers are in high demand. But there is a shortage of them, making it difficult for organizations to hire top talent to fill this vital role. But what, exactly, is a data engineer? And how do you pursue a career in this high-demand field?
What does a data engineer do?
Data engineers are a critical role on the DataOps team. They are responsible for building the systems and infrastructure that collect, validate, and prepare the data for use across the business by data analysts and data scientists. They also build and maintain data pipelines, and ensure compliance with their organization’s governance and security policies.
The day-to-day of a data engineer can be varied, but often includes activities such as:
- Acquiring and transforming data sets into usable data products for the business
- Maintaining data pipelines to ensure clean and continuously-updated data can flow smoothly with minimal intervention required
- Reviewing data and pipelines to ensure they remain compliant with governance and security policies
- Supporting the data ecosystem by assessing and deploying DataOps tools
- Collaborating with business partners and company leaders to understand the goals and objectives of the business, and to ensure they are met by the data infrastructure
What does a data engineer career path look like?
The career path for data engineers is evolving. While many colleges and universities today offer degrees in data science, far fewer offer programs that focus on data engineering. In fact, many data engineers acquired their skills through a patchwork of courses and certifications obtained outside of – or alongside – their college degree.
As well, many data engineers started their careers as software engineers. Because many of the principles and skill sets are the same, software engineers looking for a change saw data engineering as a logical step in their career path. In fact, many organizations today are retraining their software engineers and finding great success with this approach.
Data engineers can be entry-level roles, but depending on the organization, they can also require more experience and expertise. Data engineers can also progress through the ranks, becoming DataOps leaders and even the Chief Data Officer.
What skills does a data engineer need?
Data engineers often possess a unique blend of skills ranging from programming languages to database design to the development of data pipelines.
In addition, data engineers need a solid understanding of the following:
- Programming languages, like Python and SQL
- SQL and NoSQL databases
- ETL/ELT technologies such as dbt, Matillion, and Fivetran
- Streaming like Apache Kafka
- Infrastructure, including cloud infrastructure
How to become a data engineer
Earlier this year, we predicted that data engineers will become an even hotter commodity than they were last year. But if you are interested in becoming a data engineer, where do you start?
1. Assess your skills and identify your skill gaps
Start by understanding the full range of your skills and identify which ones apply to the role of a data engineer. Once you know what skills you have, then you need to determine what skills you’re missing.
2. Make a plan to fill your gaps
If you identify gaps in your skillset, make a plan to fill them. Explore courses and certifications that provide training and education that help you round out your experience. Some colleges and universities offer these classes, but you should also explore platforms such as EdX, Coursera, and Udemy.
3. Get experience
Once you’ve rounded out your skillset, then it’s time to put theory into practice. Apply your skills to a project or initiative where you can gain some practical experience. Many times, courses offer practical ways to apply your newly-acquired skills and build your portfolio. But you can also explore free resources online to get your feet when in the data engineering space.
Data engineers are a critical role in any data organization. And the demand for skilled data engineers is growing larger every day. As data engineers continue to be a sought-after resource, we’ll see more organizations explore creative ways to fill these gaps.