A career as a big data engineer requires education and work experience, with many professionals opting to get certified. Discover what big data engineers do, what the job opportunities are, and how to get started.
If you're interested in data, math, analytics, problem-solving, or information technology, working as a big data engineer could be an excellent career choice. As technology makes it possible to collect more data than ever, companies need big data engineers to help them capture, store, and transport it so they can make sense of it.
Explore big data science and how you work with organizations to improve their data pipelines as a big data engineer. Learn about potential earnings, skills, job outlook, and how you can start your career.
course
Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big ...
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Average time: 18 hour(s)
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Skills you'll build:
Big Data, Data Analysis, Data Management, Cloud Computing, Data Structures, Databases, Machine Learning
A big data engineer is a professional who is responsible for developing, maintaining, testing, analyzing, and evaluating a company's data. Big data refers to extremely large data sets. In the modern economy, it is common for companies to collect large volumes of data throughout the course of conducting their business operations.
When used correctly, big data can be highly beneficial for organizations to help them improve efficiency, profitability, and scalability. However, companies' big data is not helpful unless a big data engineer builds the systems to collect, maintain, and extract data. So, big data engineers ultimately have the responsibility of helping companies manage their big data.
The most significant difference between big data engineers and data scientists is that big data engineers are primarily responsible for building and maintaining the systems and processes that collect and extract data. Data scientists analyze the cleaned data to generate insights, using various predictive models to create meaningful insights.
Read more: What Is a Data Scientist? Salary, Skills, and How to Become One
All of the following are typical job responsibilities for big data engineers:
Designing and implementing software systems
Creating systems for collecting data and for processing that data
Using Extract Transform Load operations (the ETL process)
Creating data architectures that meet the requirements of the business
Researching new methods of obtaining valuable data and improving its quality
Creating structured data solutions using various programming languages and tools
Mining data from multiple areas to construct efficient business models
Collaborating with data analysts, data scientists, and other teams
course
Start your journey in one of the fastest growing professions today with this beginner-friendly Data Engineering course! You will be introduced to the core ...
4.7
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Beginner level
Average time: 13 hour(s)
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Skills you'll build:
Data Management, Databases, Network Security, Big Data, Leadership and Management, SQL
According to ZipRecruiter, the average salary of a big data engineer is $131,001 [1]. Highly experienced big data engineers in the latter stages of their careers can make significantly more than that. However, those just entering the field who do not have a high level of experience can expect to make less.
The US Bureau of Labor Statistics (BLS) places the job title big data engineer in the categories of statisticians and computer and information research scientists. Examine the job outlook for each of these two categories:
Statistician: Projected job growth of 11 percent between 2023 to 2033 [2]
Computer and information research scientist: Projected job growth of 26 percent between 2023 and 2033 [3]
According to the BLS projections, the job of a big data engineer is likely to increase in demand significantly in the next few years, making this career a good career path to pursue.
Big data engineers commonly possess all of the following skills:
Computer programming with languages like C++, Java, and Python
Databases and SQL
ETL and data warehousing
Talend, IBM DataStage, Pentaho, and Informatica
Operating system knowledge for Unix, Linux, Windows, and Solaris
Apache Spark
Data mining and modeling
If you know Python and you're looking to gain the skills and experience you need to become a big data engineer, consider enrolling in DeepLearning.AI's Data Engineering Professional Certificate program:
professional certificate
Learn the principles of effective data engineering. Build your skills in the high-demand field of data engineering and learn how you can deliver real business value by applying a core set of principles and strategies for developing data systems.
4.8
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15,917 already enrolled
Intermediate level
Average time: 3 month(s)
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Skills you'll build:
Data Management, DataOps, Data Warehousing, Data Modeling, Data Management Platforms, Data Architecture, Data Transformation, Data Engineering, Data transformation, Data Orchestration, The principles of good data architecture, Requirements Gathering, AWS cloud fundamentals, Thinking like a data engineer, Translating requirements into tool and technology choices, Feature Engineering, Spark and PySpark, Networking on the Cloud, Batch and Streaming Ingestion, Data orchestration, Infrastructure as Code (IaC), Advanced SQL, Data warehouse / data lake / data lakehouse architectures, Data storage fundamentals, Streaming queries with Apache Flink
Most people complete these several steps on their journey to becoming a big data engineer.
If you want to become a big data engineer, you will have to master all the technical skills mentioned above, which translates into a lot of education. Many people who become big data engineers have bachelor’s and master’s degrees in a related field, such as computer science, statistics, or business data analytics.
Big data engineers need to be masters of coding, statistics, and data. Most companies require a bachelor’s degree for big data engineer positions.
Read more: How Long Does It Take to Get a Bachelor’s Degree?
Experience is a valuable asset for obtaining a job as a big data engineer. You can gain experience by freelancing, interning, practicing independently, or working in related positions. The more experience you get, the better your chances of obtaining a big data engineer position.
Obtaining Professional Certificates can also be highly beneficial for securing employment as a big data engineer. Each of the following certificates can be helpful for people who are trying to become big data engineers:
Cloudera Certified Professional (CCP) Data Engineer
Associate Big Data Analyst (ABDA)
Google Cloud Certified Professional Data Engineer
professional certificate
Prepare for a career as a data scientist. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from IBM. No prior experience required.
4.6
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695,216 already enrolled
Beginner level
Average time: 4 month(s)
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Skills you'll build:
Generative AI, Data Science, Model Selection, Data Analysis, Python Programming, Data Visualization, Predictive Modelling, Numpy, Pandas, Dashboards and Charts, dash, Matplotlib, Cloud Databases, Relational Database Management System (RDBMS), SQL, Jupyter notebooks, Machine Learning, Clustering, regression, classification, SciPy and scikit-learn, CRISP-DM, Methodology, Data Mining, Github, Jupyter Notebook, K-Means Clustering, Data Science Methodology, Rstudio, Big Data, Deep Learning, Quering Databases, Data Generation, Career Development, Interviewing Skills, Job Preparation, Resume Building
Big data engineering is a fast-growing career that combines engineering skills with data science to create solutions for the collection and processing of massive amounts of data. If you have a passion for computer science, data, numbers, and programming, then a career as a big data engineer could be the perfect choice for you. With the IBM Data Engineering Professional Certificate, you can achieve your career goals in big data.
professional certificate
Prepare for a career as a Data Engineer. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from IBM. No prior experience required.
4.6
(5,505 ratings)
112,057 already enrolled
Beginner level
Average time: 6 month(s)
Learn at your own pace
Skills you'll build:
Generative AI, Database Security, Database (DBMS), Database Servers, database administration, Relational Database, Cubes, Data Warehousing, Snowflake Schemas, Data Lakes, Rollups, Data Marts, Star Schemas, Cloud Database, Mongodb, Cassandra, NoSQL, Cloudant, Machine Learning, Machine Learning Pipelines, Data Engineer, SparkML, Apache Spark, Big Data, SparkSQL, Apache Hadoop, Information Engineering, Querying Databases, Data Generation, Convolutional Neural Networks, Extract Transform and Load (ETL), Apache Kafka, Apache Airflow, Data Pipelines, Data Science, Data Analysis, Python Programming, Numpy, Pandas, Business Intelligence, Data Visualization, IBM Cognos Analytics, Google Looker Studio, Dashboards, Database (DB) Design, Postgresql, Relational Database Management System (RDBMS), Database Architecture, MySQL, Shell Script, Bash (Unix Shell), Linux, Linux Commands, Relational Databases, SQL, Web Scraping, Cloud Databases, Jupyter notebooks
Zip Recruiter. “Big Data Engineer Salary, https://www.ziprecruiter.com/Salaries/Big-Data-Engineer-Salary#Yearly." Accessed November 11, 2024.
US Bureau of Labor Statistics. “Mathematicians and Statisticians: Occupational Outlook Handbook, https://www.bls.gov/ooh/math/mathematicians-and-statisticians.htm." Accessed November 11, 2024.
US Bureau of Labor Statistics. “Computer and Information Research Scientists: Occupational Outlook Handbook, https://www.bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm." Accessed November 11, 2024.
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