How to Hire Big Data Developers: Key Things You Need to Know

Today Big Data seems to be practically everywhere. As business these days is practically fully digitalized, there is a severe need to have the possibility to process vast volumes of data seamlessly and correctly. Big Data analytics help streamline numerous business processes, enhance decision-making and ensure better reporting. This is precisely what a company needs to have to gain an additional competitive advantage and strengthen its position in the market. That’s why it is obvious why many companies today want to have access to the skills of a big data engineer (or engineers).

If you are also looking for a big data developer for your project and want to know how to find the best professionals, reading this article is exactly what you should start with. So here we are going to share the tips that will help you to understand what factors you should bear in mind to make the right choice.

Demand for Big Data Solutions and Positions: Statistics

But before we proceed to some practical recommendations on how to hire a data engineer, we offer you to look at some figures that prove the growing influence of Big Data on the current software market.

By 2022, the global big data industry volume will reach $274.3 billion. According to other analysts, the market will be valued at $307.52 billion in 2023 and will grow up to $745.15 billion by 2030. The figures are quite impressive, but not surprising as companies and organizations (and individuals) have to deal with a lot of data daily. For example, according to the research, in 2023, the volume of generated data is expected to hit 120 zettabytes. Just imagine: in 2021, this figure was at the level of 79 zettabytes. And it is projected that 2025 this volume will equal 181 zettabytes. But the issue is that nearly 80% of all the generated data remains unstructured.

Due to low data quality, the annual losses of the US economy are around $3.1 trillion.

Data Development Will Increse by up to 180 Zb by the Year 2025

https://www.statista.com/statistics/871513/worldwide-data-created/

But the good news is that businesses have started to realize the importance of proper data handling. For example, 95% of companies that took part in the studies admitted that the management of unstructured data is one of the problematic tasks for them. And already, over 90% of businesses are investing in Big Data and AI today.

The interest in Big Data solutions leads to the growing demand for engineers who work with these technologies. Big Data jobs were among the most highly demanded in 2022. In 2022 96% of businesses were planning or likely to consider hiring data engineers and other experts with relevant skills who can work with big data analytics. And in 2023, we can still observe an increased demand for considerable data-related skills.

What are the Benefits of Big Data Analytics for Businesses?

What are the benefits of big data analytics? How can your business enjoy them? Read our post to find answers and build the right strategy!

What Does a Big Data Engineer Do?

A big data developer is a specialist responsible for building and maintaining big data-powered systems. This specialist must also code, design, test, and support apps dealing with data processing (Hadoop apps) to help companies reach their business goals.

That’s probably the most generic reply that we can provide to the question mentioned above. However, let’s try to go into more detail. The most typical tasks for such an expert can be:

• to create algorithms for presenting vast volumes of data in the form of clear and valuable info that can be further applied for solving different tasks;
• to develop database architectures and additionally maintain them;
• to build new methods of validating data and create new data analytics tools for various needs;
• to modernize data processing solutions following the latest Big Data trends when it is necessary;
• to make sure that data processing is executing in full accordance with security and  data governance policies;
• to monitor the performance of existing programs and estimate their efficiency and accuracy;
• to participate in the creation of documentation and best practices;
• to share their knowledge and educate other employees on the ways to use the offered technologies.

Of course, the list of responsibilities of a software engineer (Big Data) also includes close communication with the company’s management (to understand business goals) and other engineers and developers (to make sure that all tech experts are on the same page).

In general, data-related services can include:

• Big Data storage,
• Big Data mining,
• Big Data Automation,
• Big Data visualization,
• Big Data management,
• Big Data Migration,
• Big Data Integration,
• Big Data development,
• Consulting.

Big Data App Development: Benefits, Peculiarities, and Pitfalls

If you are interested in Big Data application development, we recommend reading this article to know how to prepare for this process.

What Skills Should a Big Data Developer Have?

Actually, as well as any other software developer, a big data engineer should understand the technologies and programming languages used in this domain. But that is only the tip of the iceberg.

Working with Big Data is much more than just programming apps (though it is also required). Knowledge of frameworks or Hadoop-based technologies, as well as SQL and NoSQL-based technologies, is a must. But what else?

Among other essential skills, we can also name:

• Data visualization skills.
• Strong analytical skills.
• Familiarity with data mining.
• Knowledge of machine learning algorithms.
• Problem-solving and creative thinking ability.
• Understanding of general business processes.
• Multi-tasking.
• Good interpersonal skills.
• Strong organizational and planning skills.
• Pro-activity.

What Tech Stack is Popular in Big Data Solution Development?

The Big Data tech stack is quite impressive. Below, you can find just the most popular technologies used today:

• Programming languages: Python, Java, Scala, and C++;
• Big data processing tools: Spark, Kafka, Flink, Storm, Hadoop MapReduce, Druid, Apache Giraph;
• Data storage: Apache Hadoop, GCP Cloud Storage, Amazon S3, Azure Data Lake;
• Databases: Azure Cosmos DB, Azure Synapse Analytics, Cassandra,  Apache Hive, Apache HBase, Apache Nifi, Amazon Redshift, Amazon DynamoDB, MongoDB;
• Data management: Talend, Informatica,  Apache Airflow, Apache Zookeeper.

And of course, that’s far from a full list of all the technologies used in working with Big Data and your tasks may require the knowledge of some other tools and frameworks.

Data Engineer Hiring Guide: Practical Tips

As well as in the case with any other IT experts, you always have a choice: you can employ them at your company and have your own in-house software development team, or you can opt for one of the outsourcing models and get access to the global pool of talents. You can hire a whole development team or just a couple of specialists if you need to expand your already created team with specific skills and knowledge.

But regardless of the chosen option, there are a couple of things that you shouldn’t forget about.

1. Do not save money when you need to hire Big Data developers. When processing and storing huge volumes of sensitive and strategically essential data, you should ensure that the system is fully protected and secure. It means that there is no space for mistakes and human errors. Try to find the best specialists with proven expertise.
2. Set clear requirements. Before starting work on your project, a big data developer should clearly understand your specific needs, goals, and expectations. The more detailed requirements and explanations you provide, the more chances you will hire specialists who can precisely tackle your needs. This rule is equally important in both cases when you try to find experts on your own and when you want to establish relations with an outsourcing company.
3. Define all specific requirements, if any. So often, at the stage of data engineer hiring (especially when it comes to staff augmentation or working with a dedicated team), companies can easily forget about specifying such moments as working hours or English level. However, when cooperating with specialists from other countries and continents, discuss working hours due to possible time differences. Often, developers agree to change their traditional working hours to make it comfortable for you to communicate with them.
4. If you are looking for a specialist for at least one project, specify the set timeframes. Then, developers should clearly understand when you will need their help and plan their time and work on their previous and future projects properly.
5. Plan your budget. The rates should be discussed already at the stage of hiring. Both sides should realize each other’s expectations and possibilities from the very beginning. Moreover, when hiring Big Data architects/developers, we strongly recommend you be very attentive to the contracts and agreements you sign. All financial terms should be clearly stated there.
6. Do not hesitate to ask questions. If you can communicate directly with a Big Data devops engineer before approving this candidate, never miss this chance. Thanks to direct communication with a person, you will get a lot of valuable information regarding the previous experience of this Big Data engineer/architect, the business domains that he or she has worked in, and other background knowledge and skills. Quite often, such interviews can tell you much more than all the CVs of Big Data developers for hire.
7. Provide feedback. This tip is more relevant when you have already started working with a Big Data software engineer. Nevertheless, you should bear it in mind from the very beginning. Specialists who are working on your project should always know whether they are on the right track, whether their work corresponds to your expectations, and whether they have understood your tasks and your requirements fully correctly. Regular feedback is necessary if you want your project to be finished on time.

Benefits of Hiring Big Data Developers at Geomotiv

If you are looking for seasoned software engineers, our company can be a perfect place to hire such experts. And there are some strong arguments in favor of this thesis.

• Excellent price and quality ratio. We respect your time and money and offer only high-quality, reasonably-priced services that do not incur additional costs and losses.
• Well-organized business processes. The years of working in the software development industry helped us gain solid experience in establishing all the strategies to be entirely comfortable for both developers and clients. As a result, we know how to build all the procedures seamlessly and can foresee any potentially problematic issues to react to them quickly and efficiently.
• Vast talent pool. We are proud to have only really talented and experienced engineers on our team. Almost all our Big Data engineers are senior developers who have been working in this field for nearly ten years. They have a perfect understanding of all the industry standards and requirements and transform their knowledge into software products that bring real value.
• Fast hiring. Very often when a company decides to hire Big Data engineer that will join an in-house team, the entire recruiting and onboarding process can take up to several months. With Geomotiv, you can hire remote Big Data developers significantly faster. Thanks to our smooth processes and access to a great number of outstanding specialists, we can find experts with the required skills within a couple of weeks. It means that within 2-3 weeks after we get your requirements, a Big Data system engineer (or engineers) will join your project.
• Rich expertise. Our experience is not limited to a couple of finished courses or reading books on Big Data. You can find an impressive amount of successfully built and implemented projects in our portfolio. For instance, our experts have created a system that can generate 2.5 terabytes of behavior logs and 17 terabytes of marketing data a day. And all this data is further used for yield management. And that’s only one example! You can read more about other projects here.
• Readiness for projects of any complexity. We are not afraid of challenges and have never rejected a project because it looks too complicated. On the contrary, our developers can cope with any task! And what is more important, they always look not just for any solution but for the best one that will perfectly meet your goals and requirements.

Our Experience in Big Data and Analytics

Regardless of whether you are looking for a junior Big Data engineer, a senior Big Data engineer, or you want to hire a group of specialists, at Geomotiv, we will be happy to help you and support you at any stage of your project. Moreover, we have rich expertise in this sphere.

One of the examples of our work was the development of a programmatic platform for AdTech transactions that was intended for helping customers to get rid of obsolete approaches. In half a year, we built a horizontally scalable system that can successfully cope with peak loads up to 20K QPS. The platform has a full-stack AdTech functionality, including an advanced reporting tool. Read the full case study here.

Programmatic AdTech platform Adoppler

https://adoppler.com/

Another case that can be interesting for you to learn about is the creation of an automated email marketing platform for niche digital-to-direct sphere operations. When the client came to us, they already had a Python-based solution that couldn’t provide scalability following the continuously growing demand. That’s why it was decided to fully rebuild the platform and equip it with new web features. On this project, we had to support the functionality of the platform’s first version and build a new one using our Big Data skills. The second version of the platform fully met the set requirements and helped the client to reduce the expenses on software support services.

Conclusion

It doesn’t matter whether you are a huge corporation or a small startup. You should always try to find the best experts in the respective field. That’s why once you’ve decided to hire big data developers, plan the hiring process correctly, and make sure that potential candidates meet all your requirements. With professional big data engineers, the functioning of your tech infrastructure will be entirely seamless, and you will see its positive impact on your business growth and expansion.

In case you have any questions about our services or models of cooperation with Geomotiv, do not hesitate to contact us.