What is a data engineer? An analytics role in high demand
What is a data engineer?
Data engineers are responsible for finding trends in data sets and developing algorithms to help make raw data more useful to the enterprise. This IT job requires a significant set of technical skills, including a profound information on SQL database design and numerous programming languages. In any case, data engineers also need communication skills to work across departments to understand what business leaders want to gain from the company’s large datasets.
Data engineers are often responsible for building algorithms to help give easier access to raw data, yet to do this, they have to understand company’s or customer’s objectives. It’s important to have business goals in line when working with data, especially for companies that handle large and complex datasets and databases.
Data engineers also need to understand how to optimize data retrieval and how to develop dashboards, reports and other visualizations for stakeholders. Depending on the organization, data engineers may also be responsible for communicating data trends. Larger organizations often have multiple data analysts or scientists to help understand data, while smaller companies might rely on a data engineer to work in both roles.
The data engineer role
According to Dataquest, there are three main roles that data engineers can fall into. These include:
- Generalist: Generalists are typically found on small teams or in small companies. In this setting, data engineers wear many hats as one of the few “data-focused” people in the company. Generalists are often responsible for every step of the data process, from managing data to analyzing it. Dataquest says this is a good role for anyone looking to transition from data science to data engineering, since smaller businesses won’t need to worry as much about engineering “for scale.”
- Pipeline-centric: Often found in midsize companies, pipeline-centric data engineers work alongside data scientists to help make use of the data they collect. Pipeline-centric data engineers need “in-depth knowledge of distributed systems and computer science,” according to Dataquest.
- Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. Database-centric data engineers work with data warehouses across multiple databases and are responsible for developing table schemas.
Data engineer responsibilities
Data engineers are tasked with managing and organizing data, while also keeping an eye out for trends or inconsistencies that will impact business goals. It’s an exceptionally technical position, requiring experience and skills in areas like programming, mathematics and software engineering. However, data engineers also need soft skills to communicate data trends to others in the organization and to enable the business to make use of the data it collects. Some of the most widely recognized responsibilities for a data engineer include:
- Develop, construct, test and maintain architectures
- Align architecture with business requirements
- Data acquisition
- Develop data set processes
- Use programming language and tools
- Identify ways to improve data reliability, efficiency and quality
- Conduct research for industry and business questions
- Use large data sets to address business issues
- Deploy sophisticated analytics programs, machine learning and statistical methods
- Prepare data for predictive and prescriptive modeling
- Find hidden patterns using data
- Use data to discover tasks that can be automated
- Deliver updates to stakeholders based on analytics
Data engineer salaries
According to Glassdoor, the average salary for a data engineer is $137,776 per year, with a reported salary range of $110,000 to $155,000 depending on skills, experience and location. Senior data engineers earn an average salary of $172,603 per year, with a reported salary range of $152,000 to $194,000.
Here’s what some of the top tech companies pay their data engineers, on average, according to Glassdoor:
|Company||Reported salary range||Average annual salary|
|Amazon||$78,000 – $133,000||$103,849|
|Hewlett-Packard||$64,000 – $105,000||$86,164|
|$93,000 – $171,000||$122,695|
|IBM||$90,000 – $116,000||$99,351|
Data engineer skills
The skills on your resume might impact your salary negotiations — in some cases by more than 10 or 15 percent, depending on the skill. According to data from PayScale, the following data engineering skills are associated with a significant boost in reported salaries:
- Scala: +17 percent
- Apache Spark: +16 percent
- Data warehouse: +14 percent
- Java: +13 percent
- Data modeling: +12 percent
- Apache Hadoop: +11 percent
- Linux: +11 percent
- Amazon Web Services (AWS): +10 percent
- ETL (extra, transform, load): +7 percent
- Big data analytics: +6 percent
- Software development: +2 percent
Becoming a data engineer
Data engineers typically have a background in software engineering, engineering, applied mathematics or have a degree in other related IT fields. Since the job requires heavy technical information, aspiring data engineers may find a bootcamp or certification alone won’t cut it against the competition. Most data engineering jobs need at least a relevant bachelor’s certificate in a related discipline, according to PayScale.
You’ll require involvement in numerous programming languages, including Python and Java, and information on SQL database design. On the off chance that you already have a background in IT, or in a related discipline such as mathematics or analytics, a bootcamp or certification can help tailor your resume to data engineering positions. For example, on the off chance that you’ve worked in IT yet haven’t held a specific data work, you could join up with a data science bootcamp or get a data engineering certification to prove you have the skills on top of your other IT information.
On the off chance that you don’t have a background in tech or IT, you may need to try out an inside and out program to demonstrate your proficiency in the field or invest in an undergraduate program on the off chance that you don’t have a degree. On the off chance that you have an undergraduate certificate, however it’s not in a relevant field, you can always investigate master’s programs in data analytics and data engineering.
Ultimately, it will rely upon your situation and the types of jobs you have your eye on. Take time to browse employment opportunities to see what companies are looking for, and that will give you a better idea of how your background can fit into that job.