If you’re looking to move into a red-hot, rapidly growing industry with a variety of career options, then you might want to explore data engineering. Becoming a data engineer allows you to influence the decisions organizations make about their future.
What Does a Data Engineer Do?
Data engineering involves making sense of the large quantities of data companies collect in the course of doing business. It focuses on data infrastructure, including finding, transforming, validating, and storing data.
The work performed by data professionals contributes to endeavors like building infrastructures that power database systems, fueling technologies like AI analytics, machine learning, and data science. Data engineers build ecosystems that organize data then use analytics tools to transform the information and provide access to the insights discovered.
Data engineers rely on specific resume skills to perform their duties. They’re fluent in programming languages like Python, R, and Java, offer expertise in Microsoft SQL and NoSQL systems, and are familiar with big data tools like Hadoop, MapReduce, and Apache Spark. Many organizations rely on information from data engineers to fuel various processes and drive business decisions. They play a key role in positioning companies for the future by finding trends in company data.
State of the Data Engineering Job Market in 2021 Source: Dice
Requests for data engineer postings grew by 50% year over year, according to the 2020 Dice Tech Job Report. One of the major drivers of the growth is the spread of data innovation centers around the country.
Aspiring data engineers don’t have to head to Silicon Valley to find a job. It’s possible to find a position in places like Ohio, Florida, and Georgia. Springboard’s data engineering bootcamp teaches you the skills to make you a viable candidate for a job in the field.
Top 3 Data Engineering Jobs in 2021
Below are 3 top positions available from companies looking for candidates to fill data engineering job roles.
1. Data Warehouse Engineer
Companies relying on data to drive business decisions and need people who can bring information together, making it available throughout an organization. Data warehouse engineers build, manage, and execute strategies for data warehouses. They’re often called upon to perform functions like:
- Ensuring an organization’s data needs are fulfilled
- Selecting the right data engineering tools to execute various data processes
- Outlining the scope of different data projects
- Overseeing the quality of data warehouse projects
- Storing and overseeing the data pulled from various sources
Communication, organization, and the ability to see the big picture are essential soft skills for data warehouse engineers. They often work with other teams to come up with ideas then take responsibility for turning them into a viable solution.
Data warehouse engineers need technical skills like:
- Data management
- Data backup knowledge
- Building data pipelines
- Creating data models
- Maintaining data quality
Data engineers often work with other team members to generate ideas and then assume responsibility for turning them into viable solutions. For that, they rely on soft skills like:
- Ability to see the big picture
According to Glassdoor, the average salary for a data warehouse engineer is $118K.
Expected Job Growth Outlook:
According to Dice, job postings for data warehouse developers increased by 52% between February and March of 2021, showing a growing need for individuals with data warehouse engineer skills.
2. Analytics Engineer
Analytics engineers support individuals working as data scientists, engineers, and analysts to improve data utilization within an organization and perform their jobs efficiently. They maintain responsibility for building and maintaining datasets relied upon by data scientists and analysts. Analytics engineers are usually responsible for:
- Cleaning data compiled by a data engineer to ensure it complies with best data hygiene practices
- Coordinating with data engineers to expedite the data cleaning process
- Helping with the design and development of analytics projects
- Working with other technology teams to create and maintain databases
- Developing and implementing tools, processes, and algorithms for data mining
The skillset of an analytics engineer typically includes:
- Data warehousing
- Data extracting
- Data modeling
- Software engineering
- Using tools like Redshift, BigQuery, Snowflake, and dbt
Glassdoor lists the average salary of a data analytics engineer as $110K.
Expected Job Growth Outlook:
The Data Council sees the role of analytics engineer as either a stepping stone to other lucrative fields in data science or a possible career alternative. However, since the position only emerged within the last few years, they believe it will take time to see how the field evolves.
3. Data Architect
Every data project requires someone capable of taking the concepts outlined in a business requirement and translating them into a technical template with defined principles and data standards. With so many organizations expanding their use of data, data architects should remain in demand for years to come. The role typically requires you to:
- Create technical specifications for business requirements
- Build a framework for data architecture that includes details like modeling, security, and metadata
- Define the flow of data within an organization, including where it comes from and which areas require it to function
- Coordinate with departments, vendors, business partners, and stakeholders
Data architects rely on skills like:
- Data modeling and design
- System development
- Reporting technology
- Databases, including relational and NoSQL
- Unstructured data
- Predictive analytics
- Data visualization
The average data architect salary is $121,198, according to PayScale.
Expected Job Growth Outlook:
According to Robert Half Technology, demand for data architects should only intensify since data plays such a central role in many organizations’ decision-making.
Ready to switch careers to data engineering?
Data engineering is currently one of tech’s fastest-growing sectors. Data engineers enjoy high job satisfaction, varied creative challenges, and a chance to work with ever-evolving technologies. Springboard now offers a comprehensive data engineering bootcamp.
You’ll work with a one-on-one mentor to learn key aspects of data engineering, including designing, building, and maintaining scalable data pipelines, working with the ETL framework, and learning key data engineering tools like MapReduce, Apache Hadoop, and Spark. You’ll also complete two capstone projects focused on real-world data engineering problems that you can showcase in job interviews.
Check out Springboard’s Data Engineering Career Track to see if you qualify.