The Day-to-Day as a Data Engineer
Data Engineers create the infrastructure for data and format data into a useful system that Data Scientists use to analyze large amounts of data. Data Engineers can specialize in pipelines, databases or platforms, warehouses or infrastructure, or be generalists. They work with Data Scientists, upper-level management, Data Analysts, Developers, Data Architects, DevOps Engineers, Database Administrators, and Database Architects. Data Engineers work a typical 40-hour week.
Data Engineers can find work at companies or on projects focusing on artificial intelligence (AI), software, data analytics, healthcare, IT, retail, marketing, government, transportation, science, and more. They can find full-time employment onsite or remotely. Each day is different for a Data Engineer, but you might find them writing queries, creating data pipelines, coding, architecting data stores, combining data sources, or meeting with Data Scientists.
What Skills Should Data Engineers Have?
Data Engineers must know how to create reliable data pipelines, architect distributed systems, combine data sources, write queries, wrangle data, optimize systems, engineer for scale, and architect data stores. A strong foundational understanding of the extract, load, transform methodologies (ELT) is also expected. Collaborating with data science teams to build the right solutions for them will require strong communication skills with both non-technical and data-skilled staff members.
Tools, like Hadoop, Spark, Kafka, and Hive, will be useful for a Data Engineer. Coding is a large part of the role of Data Engineer; they must know SQL at a minimum and might find learning more languages, such as Scala, R, and Python, valuable, as each company will have their own preferred coding languages. Data Engineers should also know the major database systems that companies use, such as MySQL, MongoDB, Postgres, Cassandra, and Oracle. Some companies are converting to cloud-based services and some Data Engineers will need to know cloud infrastructure best practices for services such as Amazon Web Services (AWS), Google Cloud, or Microsoft Azure. Not all Data Engineers will need to know these skills.
It is important for a Data Engineer to have strong foundational knowledge in a wide variety of tools to rely upon when choosing the proper technology for their company’s needs. Tools can be and often are, learned on the job, while concepts are something a Data Engineering candidate must be proficient in before applying for anything.
Learn the Skills You Need to Become a Data Engineer
-
Data Science
Data science combines domain knowledge, programming skills, mathematics, and statistics to infer crucial insights from data. These insights can be used by businesses, governments, and any other data-collecting entities to inform decisions.
-
Python
Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. It is used to write scripts, automations, algorithms, manipulate data, and create frameworks. Python prioritizes simplicity, easy to learn syntax, readability, and versatility.
-
SQL
SQL stands for Structured Query Language. It is a computer language used to store, manipulate, and retrieve data which is stored in a relational database.
-
Machine Learning
Machine learning is the use and study of computer algorithms that improve automatically through experience. It is a subset of artificial intelligence (AI). Machine learning is used in everything from email filtering to Netflix recommendations.
-
R Programming
R is a programming language and free integrated development environment (IDE) for statistical computing and graphics. R is most commonly used by Data Scientist and Statisticians for developing statistical software and data analysis.
-
Mathematics
Mathematics are used on a day-to-day basis by many technical positions. Subjects like linear algebra, calculus, statistics, and probability are used by Data Scientists, Cybersecurity professionals, Developers, Motion Graphics Designers, Engineers, and more.
Data Engineer Salaries
A Data Engineer in the United States makes, on average, $129,415 annually, according to Indeed.com.
Salaries for Data Engineers vary by region within the the United States. Listed below are some Data Engineer salaries for specific areas with the United States compared with the average national salary:
- U.S. Average $129K source n/a
-
Richmond, VA
$174K
source
+34.68%
-
San Francisco, CA
$165K
source
+27.74%
-
Greensboro, NC
$165K
source
+27.65%
-
Long Island, NY
$162K
source
+25.95%
-
Oakland, CA
$155K
source
+19.83%
-
Virginia
$151K
source
+17.45%
-
Orange County, CA
$151K
source
+16.89%
-
Los Angeles, CA
$148K
source
+14.52%
-
New York City
$146K
source
+13.39%
-
Greenville, SC
$146K
source
+13.38%
-
Columbus, OH
$144K
source
+11.39%
-
Winnipeg
$144K
source
+11.32%
-
New York
$143K
source
+10.89%
-
Dayton, OH
$141K
source
+9.67%
-
Hartford, CT
$140K
source
+8.86%
-
Phoenix, AZ
$140K
source
+8.29%
-
Seattle, WA
$139K
source
+8.09%
-
Fairfax, VA
$138K
source
+7.21%
-
Austin, TX
$138K
source
+6.69%
-
Houston, TX
$137K
source
+6.42%
-
Cleveland, OH
$137K
source
+6.21%
-
San Jose, CA
$136K
source
+5.78%
-
New Haven, CT
$136K
source
+5.51%
-
Sacramento, CA
$136K
source
+5.37%
-
Alexandria, VA
$136K
source
+5.19%
-
Minneapolis, MN
$135K
source
+4.96%
-
Portland, OR
$133K
source
+3.16%
-
Connecticut
$133K
source
+2.79%
-
San Diego, CA
$132K
source
+2.23%
-
Boston, MA
$129K
source
+0.07%
- U.S. Average $129K source n/a
-
United States
$127K
source
-1.4%
-
Baton Rouge, LA
$126K
source
-2.61%
-
Columbia, SC
$125K
source
-3.02%
-
Milwaukee, WI
$124K
source
-4.18%
-
Des Moines, IA
$122K
source
-5.45%
-
San Antonio, TX
$122K
source
-5.59%
-
Madison, WI
$122K
source
-5.62%
-
Baltimore, MD
$120K
source
-6.69%
-
Chicago, IL
$120K
source
-6.74%
-
Edmonton
$119K
source
-7.83%
-
Washington, D.C.
$119K
source
-8.04%
-
Albany, NY
$118K
source
-8.52%
-
Tampa, FL
$117K
source
-9%
-
Philadelphia, PA
$117K
source
-9.52%
-
Denver, CO
$115K
source
-10.96%
-
Calgary
$115K
source
-11.1%
-
Calgary
$115K
source
-11.1%
-
Buffalo, NY
$114K
source
-11.26%
-
Honolulu, HI
$114K
source
-11.65%
-
Oklahoma City, OK
$114K
source
-11.65%
-
San Bernardino, CA
$114K
source
-11.86%
-
Fresno, CA
$113K
source
-12.07%
-
Salt Lake City, UT
$113K
source
-12.48%
-
El Paso, TX
$113K
source
-12.54%
-
Riverside, CA
$113K
source
-12.59%
-
Charlotte, NC
$112K
source
-12.74%
-
Ottawa
$112K
source
-13.14%
-
Dallas, TX
$112K
source
-13.24%
-
Raleigh, NC
$111K
source
-13.85%
-
Nashville, TN
$111K
source
-13.87%
-
Syracuse, NY
$111K
source
-13.97%
-
Vancouver
$109K
source
-15.15%
-
Atlanta, GA
$109K
source
-15.18%
-
Inland Empire, CA
$109K
source
-15.39%
-
Pittsburgh, PA
$108K
source
-15.89%
-
Tucson, AZ
$108K
source
-15.95%
-
Montreal
$106K
source
-17.34%
-
Sarasota, FL
$105K
source
-18.39%
-
New Jersey
$105K
source
-18.62%
-
Florida
$103K
source
-19.99%
-
Tulsa, OK
$102K
source
-20.58%
-
St. Louis, MO
$101K
source
-21.24%
-
Albuquerque, NM
$101K
source
-21.75%
-
Memphis, TN
$100K
source
-22.21%
-
Orlando, FL
$100K
source
-22.66%
-
Louisville, KY
$99K
source
-23.36%
-
Quebec City, QC
$99K
source
-23.4%
-
Miami, FL
$98K
source
-23.62%
-
Toronto
$97K
source
-24.32%
-
Indianapolis, IN
$96K
source
-25.23%
-
Cincinnati, OH
$96K
source
-25.78%
-
McAllen, TX
$95K
source
-26.11%
-
Detroit, MI
$95K
source
-26.2%
-
Birmingham, AL
$95K
source
-26.58%
-
Jacksonville, FL
$93K
source
-27.99%
-
Omaha, NE
$92K
source
-28.16%
-
San Juan
$92K
source
-28.16%
-
Kansas City, MO
$91K
source
-29.06%
-
Virginia Beach, VA
$91K
source
-29.68%
-
Worcester, MA
$90K
source
-29.96%
-
Stamford, CT
$86K
source
-32.81%
-
New Orleans, LA
$85K
source
-33.93%
-
Las Vegas, NV
$84K
source
-34.76%
-
Little Rock, AR
$82K
source
-36.15%
-
Victoria
$80K
source
-37.51%
-
Knoxville, TN
$71K
source
-44.71%
-
Rochester, NY
$66K
source
-48.7%
-
Bakersfield, CA
$41K
source
-67.83%
-
Grand Rapids, MI
$16K
source
-87.55%
Typical Qualifications to Become a Data Engineer
Most employers will expect Data Engineer candidates to have a bachelor’s degree in computer science information technology, or applied math. They should also have some certifications either in database systems such as Oracle, Microsoft SQL Server, IBM, MongoDB, or Apache's Cassandra or something more general such as IBM’s Certified Data Engineer. This role typically demands at least three years of experience working with data.
Searching for Data Engineer Jobs
The job of the Data Engineer is ever-evolving and highly in-demand. They can find work at companies or on projects focusing on artificial intelligence (AI), software, data analytics, healthcare, IT, retail, marketing, government, transportation, science, and more. They can find full-time employment onsite or remotely.
Data Engineers can look for jobs on these sites:
- Dice
- Indeed
- SimplyHired
- Ziprecruiter
- Authentic Jobs
- Glassdoor
- GitHub Jobs
- Stack Overflow
- The Muse
- Crunchboard
- Startupers
- Modis
- Career Builder
- Monster
- The Ladders
- Krop
- Mashable
- Smashing
- SQL Crossing
- IT Job board
- Amazon Jobs
- Big Data Jobs
- R-Users
- USA Jobs
Data Engineers can find remote opportunities on these sites: