Hiring a Data Engineer: Job Description, Salary, & More

In today’s digital world, businesses can gather massive amounts of data, but it’s only valuable if it’s organized, structured, and interpreted meaningfully. This need has created a high demand for data engineers who can compile, manage, and draw actionable insights from large quantities of data.

Thinking of hiring a data engineer for your business? Here’s everything you need to know.

What’s a Data Engineer?

A data engineer is an IT worker who brings information from different source systems into data pipelines. The aim is to consolidate, cleanse, and optimize the data for machine learning and analytics applications so companies can make data-based business decisions.

A data engineer’s job description will change based on the industry and an organization’s needs. Larger companies tend to require more complex analytics architecture. Also, some industries, such as healthcare, financial services, and retail, are especially data-intensive.

Data Engineer Roles and Responsibilities

Specific data engineer roles and responsibilities vary based on industry and company size, but here are some typical data engineer roles and responsibilities:

Developing and maintaining large and complex datasets to meet business requirements
Designing and implementing internal process improvements to improve data quality, scalability, and efficiency
Building infrastructure to extract, transform, and load data from various sources
Designing analytical tools to interface with the data pipeline to provide actionable insights
Working with stakeholders to deliver needed data to the right parties

Top Skills of a Data Engineer

A data engineer is a technical role that also requires some soft skills, particularly the ability to communicate complex information in an easy-to-understand manner. But most importantly, a data engineer needs hard technical skills.

Data engineers need to understand database storage and warehousing. These often include SQL and NoSQL databases.
Knowledge of database management systems like Oracle, MongoDB, PostgreSQL, and MySQL are also essential.
Cloud-based warehouse technologies are critical to many data pipelines, so proficiency with platforms such as Amazon Redshift, Firebold, Snowflake, and BigQuery is important.
While less essential for entry-level positions, data engineers who work closely with data scientists need to understand data modeling, algorithms, and transformation techniques.

Other technical skills include:

Expertise in data analysis
Hands-on experience with tools such as Oracle Data Integrator and Talend Open Studio
Knowledge of business intelligence tools such as Microsoft Power BI or Tableau
Knowledge of machine learning frameworks and libraries, including Spark, PyTorch, or TensorFlow

Soft Skills

The most essential soft skills for data engineers are problem-solving and creativity. A significant part of their work is coming up with innovative solutions. They also need attention to detail, some communication skills, and the ability to break down large projects into small, achievable steps.

Qualifications

Many data engineers have a degree related to software engineering, such as computer science or IT. A master’s degree is an advantage but not a requirement to get started. There are certifications that some employers look for, such as IBM Certified Data Engineer.

Other qualifications include technical expertise with data mining, data models, and segmentation techniques, hands-on experience with some of the languages and tools listed above, and strong analytical skills.

RELATED: 8 Must-Have Data Analytics Certifications for 2023

Pay and Job Outlook

Data science is a rapidly growing field, and the need for data engineers is particularly strong. The Bureau of Labor and Statistics doesn’t have a separate listing for data engineers yet, but PayScale reports the average base pay is $95,204. But with experience and additional training, data engineers can earn up to $135,000 annually. Due to the increasing quantities of data available for businesses to process, the employment of data engineers is projected to continue to grow rapidly.

Commonly Asked Interview Questions for a Data Engineer Role

While it’s important to structure your interview to target the skills and qualifications needed for your specific role, here are a few common data engineer interview questions. In addition to general IT interview questions, you can ask:

What is data engineering?
How would you define data modeling?
What are some of the design schemas you use when performing data modeling?
Tell me about the differences between structured and unstructured data.
What are some key considerations when designing a data pipeline?
How do you ensure data security and compliance in data engineering projects?
Can you discuss a challenging data engineering project you’ve worked on and how you approached problem-solving?
What is the role of a data engineer in a data-driven organization?
Can you tell me the four Vs of big data?

Or look through this longer list of interview questions to assess data engineers.

Get Started on Hiring a Data Engineer Today

Data engineers are becoming increasingly essential to businesses. Now that customer and market data is readily available, those companies that leverage it most successfully will gain a competitive edge.

If you’re considering hiring a data engineer of any skill level, contact us today! Our skilled recruiters will qualify, interview, and vet candidates for you.