How Much Does It Cost to Hire Data Engineers?
According to one source, the average hourly rate for data engineers on Upwork is $125. However, this may vary depending on the skills, experience, and location of the data experts. Another source estimates that the total cost of hiring a software developer, including recruitment, salary, and benefits, is $142,741/year.
Again, this may differ for data engineers specifically, and for different regions and markets.
If you want to hire data specialists in India, you can check out some of the profiles and rates of data experts on Upwork or Freelancer. These platforms allow you to find and hire data engineers with various skills and backgrounds, such as data scraping, data analysis, data visualization, data management, and more.
How Much Does a Data Engineer Make?
A data engineer makes $111,998 a year in total compensation, which includes profit-sharing and bonuses in addition to their base income, according to Glassdoor. In contrast, a senior data engineer typically makes $154,989 annually in total compensation.
Is Data Engineer Still in Demand?
The field of data engineering is one that is in demand. To succeed in this sector, one must possess extensive knowledge of data and information technology. Gaining proficiency in the aforementioned data engineering abilities will position you for success when you enter this industry. The future of data engineers appears bright, and they will be in high demand given the 50% growth rate.
Hire Data Engineers
2020 saw a record high in the creation and replication of data, according to Statista. According to the same report, by 2025, the amount of data created worldwide is predicted to reach 180 zettabytes. Put differently, the industry and your business have greater access to data than ever before.
For this reason, you want to think about using experts in data science to examine this information. To get useful business insights, most firms employ data scientists, but they might not be able to provide you with the information you require on their own. Data engineers create a solid data architecture before data scientists can analyse a dataset.
To find out more about data experts and how to hire them, see our guide. We'll go over the salary range, duties, and qualifications you should seek out in a data engineer. Additionally, we'll go over how to locate and hire top personnel for data engineering.
What is a Data Engineer?
In order to prepare data for use in data science and analysis, data engineers must construct and manage the databases and systems that hold the necessary data. They also employ software engineering techniques to automate tasks like normalising, cleaning, and model-building.
A primary distinction between data science and data engineering: Making the model is one thing. However, data specialists are required to scale the model and get it operating consistently with minimum difficulty every day in order to actually get it up and running in production, performing what we want, and obtaining the dependability that we need.
"Data engineers are primarily responsible for automating and scaling processes, thereby assisting in the advancement of this field."
What is the Role of a Data Engineer?
Data engineering calls for a wide range of abilities, resources, and setups. To perform their jobs well, each of the four main categories of data experts responsibilities has to become proficient in a certain set of abilities and resources.
- All-arounders: Participates in every facet of gathering, storing, analysing, and transferring data. They need to be proficient with a variety of instruments and abilities.
- Experts in the field of data storage: In charge of establishing and overseeing big data systems (Hadoop and Spark), data warehouses (Redshift and Panoply), and relational and non-relational databases (PostgreSQL, NoSQL, and SQL).
- Experts in pipelines and programming: Generating and overseeing data flows via pipelines and scripts. A few programming languages, such as Python, Java, and C++, must be familiar to them.
What are the Skills for Data Engineers?
Data engineers also need to have soft skills. They should possess great communication and interpersonal skills, an eye for detail, the capacity to operate both alone and cooperatively in a team, strong problem-solving abilities, and the capacity to pick up new technologies rapidly. Since the profession of data engineering is always changing and evolving, data experts must also be driven to stay current on industry trends and maintain the sharpness of their abilities.
Data specialists should be able to leverage their technical expertise to think creatively and unconventionally when solving problems with data, provided they have a firm grasp of current trends.
1. Cognitive skills
After evaluating problems, data engineers create original and practical solutions. Critical thinking skills are important because you may need to come up with a solution that hasn't been thought of previously. In order to identify practical answers to issues, critical thinking is also applied in the design and debugging of data gathering and management systems.
2. Basic comprehension of machine learning and its applications
While data scientists are primarily concerned with machine learning, data engineers may find it useful to have a rudimentary understanding of using this kind of data. Increasing your proficiency with statistical analysis and data modelling can help you produce solutions that your colleagues can use, making you a valuable asset to any company.
Data engineers can be better equipped to apply their abilities to more employment options by learning about and comprehending machine learning, which is a rapidly growing discipline that applies artificial intelligence to a wide range of sectors.
3. Competencies in communication
Being a data engineer requires you to work with people who are both technical and non-technical, which is why having excellent communication skills is crucial. Even though data scientists and data architects are among the other data specialists you frequently collaborate with, you might also discuss your discoveries and recommendations with colleagues who aren't technical experts.
With remote work becoming more frequent in modern enterprises, strong digital communication skills in text, video, and audio formats are also becoming more and more crucial.
You may make yourself a highly valued asset for businesses searching for creative ways to exploit their data by developing these data engineering abilities.
What are the Technical Skills of Data Engineers?
The following abilities would be anticipated of a data engineer:
- Familiarity with big data tools like Hadoop, Kafka, and MongoDB
- Knowledge of extract, transform, and load (ETL) tools, such as Amazon Redshift, and data warehouses
- Knowledge of cloud computing platforms like GCP, AWS, and Azure
- Proficiency in Automata and Scripting
- Understanding of machine learning
- Proficiency with data transformation tools like Talend and Hevo Data
- Proficiency in fundamental data visualisation using Tableau and Excel
- Databases and tools for big data.
- Expertise in cloud computing.
- Languages used in computer programming: Java, C, C++, NoSQL, Python, R, Scala, & SQL.
- Data management, storage, mining, and aggregation.
- Data safety.
- Data transformation and ETL procedures.
Other Frequently Asked Questions (FAQs)
1. How do I recruit a data engineer?
Proficiency in programming languages such as Python, Java, and SQL is required for data engineers. Big data technologies like Hadoop, Spark, and Kafka must also be familiar to them. It also helps to have prior experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform.
Before hiring a data expert, you must ascertain precisely why you require one. Think about the knowledge gaps in your present data team, upcoming data projects, and the specific problems that your new hire will need to tackle.
2. Why hire a data engineer?
Data engineers create systems that gather, organise, and transform unprocessed data into information that can be interpreted by data scientists and business analysts in a range of contexts. Making data accessible is their ultimate objective so that businesses may utilise it to assess and improve their performance.
3. How long does it take to hire a data engineer?
Within 48 hours, you may recruit data specialists through our quick hiring process and integrate them into a fully-fledged, dedicated team. Using data-driven insights to improve decision-making and reduce costs at the outset of your project is possible when you engage with expert data engineering services.
4. Do companies need data engineers?
Whether it is hosted on-site or in the cloud, every modern organisation needs its own IT infrastructure. By creating the appropriate architecture to link data storage, sources, visualisation dashboards, & analytical tools, data engineering services offer a complete solution.
5. Is data engineer in demand?
The field of data engineering is one that is in demand. To succeed in this sector, one must possess extensive knowledge of data and information technology. When you start your career in data engineering, having a solid understanding of the aforementioned abilities can help you succeed.
Data engineering encompasses a wide range of technologies and methods that are essential for efficient data processing, and its scope is broad and ever-changing. In order to handle massive datasets effectively, it entails utilising Big Data technologies like Apache Spark and the Hadoop environment.
6. Is data engineering a well paid job?
- In India, the average yearly income for a data engineer is ₹9,45,000. In India, a data engineer's supplementary financial compensation ranges from ₹45,000 to ₹2,00,000. The average salary is ₹1,00,000.
- Glassdoor claims that data engineers frequently make over $110,000 annually (U.S.).