In today’s world, the collection and analysis of data hold significant importance. Data engineering has been a highly coveted profession for some time now, and it is predicted that its demand will surge by 50% by 2023. This applies to various industries, ranging from fashion to politics.
Given the constantly changing and dynamic nature of this field, it is not surprising that finding a Big Data Engineer can be a challenging task. The COVID-19 pandemic has accelerated the shift to new business models, and consumers have shown remarkable adaptability to these changes.
To stay ahead in the game, it is crucial for businesses to regularly review and revise their strategies, keeping in mind the ever-changing expectations and preferences of consumers. The field of ‘Big Data’ encompasses various positions related to data collection.
Unlike data analysts and data scientists who primarily analyze data (our hiring guide for data scientists is available here), a Big Data Engineer is responsible for its storage and management. The job description is often vast, making it challenging to determine the type of programmer required for a particular project.
Before we dive into the duties and responsibilities of a Big Data Engineer, let’s explore what they do and why they are a highly sought-after profession.
Defining a Big Data Engineer
Big Data Engineers play a crucial role in designing and maintaining systems that ensure the security and reliability of data. This position demands significant technical knowledge, expertise in various programming languages, as well as SQL database design. In addition to data collection, analysis, and pipeline development, Data Engineers may specialize in general computing, pipeline building, or database management.
When looking for a Big Data Engineer, it is not just about finding someone with the technical skills to collect vast amounts of data. Prioritizing which data needs to be collected to maximize its potential and application to business growth is vital. To achieve this, a Data Developer is required.
The specific duties and required expertise of a Big Data Engineer can be determined once the project’s requirements have been established.
Primary Responsibilities of a Big Data Engineer
Big Data Engineers are accountable for collecting enormous amounts of data from novel and unstructured sources. The collection process is intricate and can result in limitless datasets.
- Huge volumes of diverse and unorganized data.
- The rapid pace at which data is collected from its sources.
- Data in various formats that originates from unorganized sources.
Data Engineers are often responsible for dealing with high volumes and rapid rates of data. In this context, developers collaborate with the team to identify the most relevant data for the application and then partition it accordingly.
Data Storage Infrastructure
Big Data refers to a vast amount of data that requires organization and storage. The Data Engineer’s responsibility is to collect and arrange the data for future use in determining which information is beneficial for the business. It is crucial for the Data Engineer to review and analyze the data, even more so than the daily activities of the Data Warehouse.
It is evident that Big Data encompasses more than just an extensive database; efficient data analysis is crucial to saving valuable time and resources. If the collected data is not going to be utilized for evaluating user behavior or making predictions, it would be wise to reconsider the purpose of collecting it. Analyzing this data can aid in the growth and development of your business.
To keep up with evolving trends and customer needs, a Big Data Engineer must adapt to changes in the data collection processes. As the organization expands, so must the collected data, and the analysis techniques used to evaluate it.
Skills and Resources
When recruiting for a Big Data Engineer, it is crucial to identify the specific skill set required for the job vacancy. Therefore, the following qualifications should not be overlooked while searching for a suitable candidate.
- Apache Hadoop offers a framework for distributed storage and processing extensive data sets. It is the most commonly used technique for producing mapped results from several clusters and is also among the first open-source tools used for data collection.
- As the significance of NoSQL databases continues to increase, it becomes more critical for Big Data Engineers to have comprehensive knowledge of using them. This is due to the improved accessibility and storage of data that these databases offer, in contrast to more established options like Oracle and DB2.
- Deploying cloud clusters is a responsibility of a Big Data Engineer to manage massive volumes of data. The flexibility of the cloud allows for organizing large data sets into recognizable patterns, making them easier to identify and analyze.
- Machine Learning is not the most desirable specialization in the field of Big Data Engineering. While adding a specialist to your team may boost your system’s ability to categorize and save data, you may be wondering why you should do so.
- Apache Spark is gaining popularity for its powerful in-memory architecture widely used in big data analytics.
Advanced Skills and Expertise
From our discussion, it’s clear that frameworks are crucial when dealing with big data, rather than individual pieces of data. Consider a library without an alphabetical arrangement for books – this is similar to your data. Think of your data as a library full of books. The developers handling big data will organize the bookshelf and most importantly, create a system to categorize the books on it.
It’s crucial to keep in mind that familiarity with equipment is not the sole criterion for success when recruiting. When making hiring decisions, communication skills and a collaborative attitude should be considered. Additionally, it’s essential to remember that the selected candidate will be engaging with staff and senior management regularly, so their ability to interact with others must be taken into account.
Identifying the most appropriate candidate is crucial, but it’s equally essential to ensure that they are a good cultural fit for the organization. Data collection and analysis play a significant role in this process, and it’s imperative that the engineer can interpret and utilize the data effectively for the business’s benefit.
Identifying the necessary skills for a Big Data Developer can be challenging when recruiting. For more than 10 years, Works has been the go-to solution for numerous businesses seeking to hire top-notch remote developers and engineers, providing a better understanding of the ideal candidate. If you’re short on time or need some assurance, we can assist you with the recruitment process.