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Top 7 Data Engineering Career Opportunities in 2024
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17th Jan, 2024
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Data Science is the world's most rapidly growing sector and data engineers are at the forefront. With perhaps the promising job outlook of all data science roles, pursuing a data engineering role is the best, as with the extensive amount of data available to businesses, there is a growing need for professionals to manage, organize and analyze the data. In this article, we will understand the promising data engineer career outlook and what it takes to succeed in this role.
What is Data Engineering?
Data engineering is the method to collect, process, validate and store data. It involves building and maintaining data pipelines, databases, and data warehouses. The purpose of data engineering is to analyze data and make decisions easier. The primary process comprises gathering data from multiple sources, storing it in a database to handle vast quantities of information, cleaning it for further use and presenting it in a comprehensible manner. Data engineering involves a lot of technical skills like Python, Java, and SQL (Structured Query Language). For a data engineer career, you must have knowledge of data storage and processing technologies like Hadoop, Spark, and NoSQL databases.
Businesses rely significantly on data engineering to get meaningful insights from the vast amounts of data and take actionable decisions.
Data engineers are accountable for responsibilities, including
- Acquisition entails locating all the scattered data sets
- Cleansing entails locating and correcting any flaws in the data
- Conversion is the methodology to convert all data into a single format
- Disambiguation is the methodology of interpreting facts to be comprehended in various ways
- Deduplication is the removal of duplicate copies of data.
If you’re ready to make a career in data engineering, then the KnowledgeHut data science course content is the best choice.
What are the Data Engineer Career Opportunities?
The data engineer career path is rewarding as it empowers you to innovate and develop data applications. As data engineering is the most in-demand job in technology right now, it is a highly competitive field to break into. Candidates must have more than just technical abilities.
The position demands a solid grasp of how data and pipelines produce business value. When starting, the data engineer's role typically focuses on small initiatives. However, as the career path of data engineers advances, they get more hands-on roles in planning and strategy, with more accountability for the architecture of the data pipeline.
There are several data engineer career opportunities in the field of data engineering, ranging from entry-level positions to senior management roles to Big Data engineer career job roles. Here are the different job opportunities in the field of data engineering.
1. Data Engineer / Big Data Engineer
Data engineers create and test flexible Big Data ecosystems for businesses to run their algorithms on reliable and well-optimized data platforms. To boost database performance, data engineers also update old systems with newer or improved versions of current technology.
As a data engineer, a strong understanding of programming, databases, and data processing is necessary.
Key education and technical skills include:
- A degree in computer science, information technology, or a related field
- Expert in programming languages Python, Java, and SQL. Understanding of Big Data technologies such as Hadoop, Spark, and Kafka. Familiarity with database technologies such as MySQL, Oracle, and MongoDB.
- Analytical and problem-solving skills, excellent communication skills and the ability to work in a team.
The average salary for a Big Data engineer career in the US in 2024 is around $132,922 per year.
2. Junior Data Engineer
A junior data engineer is an entry-level position and works alongside senior data engineers to design and implement data pipelines. They also assist with data cleaning and preparation of data. Junior data engineering is the best career option for those just starting in the thriving data engineering field.
Key education and technical skills include:
- A relevant degree in computer science or a related field
- Proficiency in Python, Java, and SQL.
- Understanding of data processing frameworks such as Spark and Hadoop
- Attention to detail and outstanding communication skills
The average US salary for a junior data engineer is around $85,000 per year.
3. Senior Data Engineer
A senior data engineer is a more advanced position that involves leading the design, building, and data infrastructure maintenance. They are accountable for managing a team of junior data engineers and ensuring the data architecture meets the organization's needs.
Key education and technical skills:
- A bachelor's degree from a recognized university in computer science, information technology, or a related field
- Leadership skills, excellent communication skills and teamwork abilities
- Programming languages such as Python, Java, and SQL.
- Knowledge of Hadoop, Spark, and Kafka.
- Familiarity with database technologies such as MySQL, Oracle, and MongoDB.
The average US salary for a senior data engineer is around $150,000 per year.
4. Cloud Data Engineer
A cloud data engineer designs, builds, and maintains data infrastructures to run on cloud platforms such as AWS or Google Cloud. This data engineer career requires knowledge of cloud computing and data processing frameworks such as Apache Beam and Google Dataflow.
- A recognized degree in the related field
- Proficiency in cloud technologies such as AWS, Azure, Google Cloud, Hadoop, Spark, and Kafka
- Excellent communication, strong analytical and problem-solving skills
Cloud Data Engineers can earn an average salary of $125,000 per year
5. Data Architect
A data architect builds data management plans to readily connect, centralize, and secure with the most advanced security techniques. They work collaboratively with stakeholders to ensure data architecture meets business needs and complies with industry standards.
Key education and technical skills include:
- A degree in computer technology, or a related field
- Additional certifications in data architecture are a plus
- Knowledge of database technologies such as MySQL, Oracle, MongoDB, Hadoop, Spark, and Kafka
- Leadership skills, problem-solving skills and excellent communication skills
Data Architects can expect to earn an average salary of $124,000 per year
6. Data Warehouse Engineer
A data warehouse engineer oversees the full back-end development process for the data warehouse. Data warehouse engineers are responsible for the execution of ETL methods, cube construction for database and performance management and dimensional planning for the table structure.
Key Skills and education include:
- A degree in computer science, information technology, or a related field
- Familiarity with MySQL, Oracle, MongoDB, Snowflake and Redshift
- Strong analytical and problem-solving skills, excellent communication skills and teamwork skills.
The average salary for a data warehouse engineer is around $106,885 per year.
7. Business Intelligence Engineer
A Business Intelligence Engineer understands how data-oriented technologies work and how to manage enormous amounts of data. They also distinguish high-value data from low-value data. In simple words, they determine how Big Data can relate to meaningful business insights for the growth of businesses.
Key education and technical skills include:
- A degree in computer science or a related field
- Proficiency in BI tools such as Tableau, Power BI, and QlikView
- Understanding of MySQL, Oracle and MongoDB
- Strong analytical and problem-solving skills
The BI engineer's average salary in the US is $115,000 per year.
How Much Do Data Engineers Make?
According to Indeed, the average salary for a data engineer in the US in 2024 is around $130,000 per year. However, this can differ depending on factors such as location, experience, and industry.
What Factors Can Affect the Data Engineer's Salary?
The data engineer's salary depends on the education level, credentials, years of experience, industry, company size and location.
1. Education
Bachelor's degrees are mandated for data engineering professions. Companies may require a Master's degree or a professional Doctorate and want senior-level data engineers with demonstrated leadership abilities and industry expertise. Advanced degrees boost your earning potential by accelerating your advancement to senior positions.
2. Credentials
Specialized certifications highlight the abilities companies are looking for. Certifications from IBM, Amazon, Google, Oracle, Data Science Council of America (DASCA) Associate Big Data Engineer and Microsoft can make more money and land positions in specialized fields.
You can also check out the Data Engineer Bootcamp Certification to take your data engineering skills to the next level. With its comprehensive course content and focus on hands-on learning and practical application, you will get the opportunity to work on real-world projects and gain valuable experience in the field.
3. Level of Experience
A data engineer's salary is likely to rise as they acquire expertise. Data engineers with one to four years of experience receive an average yearly pay of $87,715. Professionals with five to nine years of experience earn $132,922 per year. With experience, you can expect to advance to more senior positions.
4. The Size of the Business
Data engineer salaries are also determined by the size of the company. Companies that provide higher salaries are bigger businesses with higher, more experienced data science teams, such as IBM, Amazon, Meta, and Google.
5. Location
Data engineers in cities with a higher cost of living can earn higher salaries than those in other cities.
Data Engineering Jobs Outlook
The most significant aspect of the data engineer career path is the current job prospects for the profession. According to the 2020 Dice Tech Jobs Report, data engineering was the fastest-growing tech employment in 2019, with a 50% increase over the previous year, outpacing all other jobs for data scientists and developers. The BLS predicted an employment data engineer career growth projection of 9% through 2031 in May 2021 which corresponds to around 11,500 new job vacancies yearly. The number of big data engineer career jobs is expected to increase by 33 percent between 2020-2030.
This significant expansion is attributable to the fact that secure data infrastructure is required for firms to deploy data mining techniques and acquire meaningful insights. Many industry's new data engineers have a background in software engineering and bring expertise in Linux, Java, SQL, Python, and Hadoop with them. As the field evolves and changes, data engineers can gain benefits by persisting to be on the cutting edge of data management innovations.
Top 8 Cities Across the Globe for Data Engineering Jobs in 2024
Location plays a significant role in the salary of a Data Engineer. Here are the top cities across the globe for data engineering jobs in 2024:
| City | Country | Average Salary |
|---|---|---|
| San Francisco | USA | $154,159 |
| New York City | USA | $140,000 |
| London | UK | £94,000 |
| Toronto | Canada | C$90,000 |
| Sydney | Australia | AU$127,000 |
| Bangalore | India | ₹1,237,608 |
| Shanghai | China | ¥300,000 |
What are the Parameters that Determine the Top Cities for AI Jobs?
1. Job Opportunities: The cities listed above have many tech companies with plenty of job opportunities in the Data Engineering field and a multitude of other tech-related jobs to boost your career opportunities.
2. A Large Talent Pool: The cities have a large pool of talented data engineers and scientists. It creates a competitive environment where companies strive to offer the best salaries and benefits to attract and retain top talent. London, New York, and Beijing have excellent job opportunities with high paychecks.
3. Strong Academic Presence: The top cities have a strong focus on research and development. These cities often have world-class universities and research institutions and attract top talent in the Data Science field across the globe.
4. Giant Tech Companies: The top cities are home to the world's largest corporations in various industries. As a data engineer, you'll find opportunities to work with companies in finance, healthcare, retail, and more. Tech giants such as Google, Microsoft, Amazon, and IBM are heavily invested in data science technology and are always in search of talented individuals to stay ahead of the competition.
5. Vibrant Startup Culture: Cities like New York, London, and Toronto have a thriving startup scene. Startups are known for their innovative ideas and cutting-edge technology. As a data engineer working on a startup, gives you the opportunity to work on exciting projects and have a significant impact on the company's success. Cities like Sydney, Berlin and Shanghai are known for their vibrant startup culture.
How to Boost Your Data Engineering Job Prospects?
There are certain skills that can help your data engineer career growth including the following.
- Learn in-demand Skills: Focus on learning skills such as cloud computing, Machine Learning, and Big Data technologies.
- Get Certified: Certification in cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform is the best way to get knowledge.
- Build a Portfolio: Build a portfolio of projects demonstrating your skills and experience.
- Network: Attend industry events and meetups to network with other professionals in the field.
- Keep Learning: Stay acquainted with the latest technologies and trends. Read blogs, attend webinars, and take online courses.
- Apply for Internships: Consider applying for internships to gain practical experience in the field.
- Create a LinkedIn Profile: Create a professional LinkedIn profile to showcase your skills and experience.
- Apply for Jobs: Apply for jobs to match your skills and experience, tailor your resume and add a compelling cover letter to each job application.
Is a Career in Data Engineering Right for You?
If you enjoy working with data and have a strong foundation in computer science and programming, a career path in data engineer is the right option for you. Here are some reasons to consider pursuing a career in this field:
- High Demand: Data engineering is a critical component of the data-driven economy and the demand for skilled data engineers will climb higher. As more organizations move towards digital transformation, the necessity for experts to build and maintain data pipelines, design and optimize databases and ensure data quality and consistency will boost.
- Lucrative Salaries: The data engineer career growth can be both highly professional and financially rewarding.
- Constant Innovation: The field of data engineering is constantly evolving, providing opportunities to learn and grow.
- Impactful Work: Data engineering plays a crucial role in managing and analyzing an organization's data. As a data engineer, you will have the opportunity to work with cutting-edge technologies, collaborate with cross-functional teams, and solve complex data problems to have a real impact on the business.
If you are passionate about technology and have the necessary skills, then a data engineer career is the right choice for you.
Summing Up
Professionals who want to boost their career graphs should always stay ahead of the competition. KnowledgeHut’s Data Science course content is hands down the best in the industry, providing all the essential skills, knowledge, and practical experience you need to excel in this field. The course covers essential topics such as data analysis, Machine Learning, data visualization, and much more. With KnowledgeHut, you will not only learn the technical skills but also the soft skills required to succeed in this field.
Frequently Asked Questions (FAQs)
1. Is data engineering a good career?
Yes, data engineering is a good career choice for students interested in technology and data. The field is growing and offers strong job prospects and salaries.
2. Is data engineering a coding job?
Yes, data engineering involves coding and programming to build and maintain data infrastructure.
3. What does a data engineer do?
A data engineer builds and maintains the IT infrastructure required to store, process and analyze large amounts of data.
4. Is data engineering a good career for the future?
Yes, data engineering is a good career choice for the future. The demand for data engineers is expected to grow as technology evolves and the amount of data generated continues to increase.
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