The Future of Data Engineering and Data Engineers

In recent years data silos have come out as a big issue for companies. Every big organization consumes a large amount of data to perform decision-making. It becomes possible with the assistance of data engineer. Data engineers play a crucial role in examining the infrastructure and performing relatable actions on it. Data Engineer future seems bright as in the future they can operate big jobs quickly owing to the computing power of various cloud data warehouse.

Evolving Role of Data Engineer

Within a decade, the role of data engineers is not limited to just an architecture builder. It is way a lot more than that. The data engineers honed with great analytical and convergent technologies understanding which draw value for companies. Data engineers are technology leaders, from handling data warehouses to IoT. Top technologies like IoT, cloud computing, AI, and ML are the pillars to plan significant development in data engineering. 

With the inclusion of Big Data, all big companies propel the role of a data engineer. Data science and big data together evolve big changes in the field within a decade. The data engineer is responsible to handle any tweak in the data pipeline with the help of data scientists. Recent years, industries have seen a comparable scope of data engineers compared to data scientists and you can understand the difference when you take the certificate in Data Science course and tackle complex Data Science problems. 

Are Data Engineers in Demand? 

Data Engineering is in great demand when we look in depth at stats. According to StitchData, every year data engineering jobs double that of the previous year. In the USA the salary of a data engineer is $116k which is comparatively higher than other jobs. The industry boon new talents that could build data products and maintain them in systems. Although the job profile is similar to software engineer's to encourage them for data engineering jobs. 

Within 2-years of span, more than 90% of data generates at an average rate of 7MB/sec/person which portrays the critical demand for data engineers. Due to massive job roles and salaries, data engineering jobs become lucrative. Data engineers are known to create data infrastructure for big companies like Uber and Spotify. 

Is Data Engineering Still a Good Career? 

Today companies understand the importance of data. Data is the main streamline rather than a byproduct. Therefore the demand for data engineers helps to identify the data process and its architecture. 

The next is, machine learning gives rise to better analysis of data which adds value to strategic functionality. Data engineers help to organize and handle piles of data for big companies.

S.no.	Countries	Salary (annual)
1.	India	Rs 7.6 lakhs
2.	UK	64321 pounds
3.	USA	$107,075
4.	Australia	$98528

Top Skills Required for Data Science Future Engineer

Skills

Java, Python, SQL, Hadoop, Linux, Database, Mysql, Data Warehousing, Business Intelligence (BI), and Big Data

Will Data Engineering Future Roles be Automated?

Yes, we could say that role of data engineering could eliminate serious outburns of data. Such that data will become more strategic and planful in making decisions hence the future role of data engineering could be automated

The Future: Where is The Data Engineer Going?

The future of data engineering includes how to make effective scaling of data which turns it less painful. In the future, data handling issues will not be a tough challenge for companies.

The data engineering role has been in the transition phase, where data is available in pipeline and warehouse centric. The future of data engineering will be automated in the next 5 years. Data will become an end-product. As a result, the data gap between the organizations and users will reduce. Demand for hybrid data infrastructures and cloud technologies will greatly affect the data engineering future scope. Data engineers will be specialized more and give a diversity of services to organizations. 

Data Roles Will Get a Board-level Seat

Data was in a primitive stage in its earlier stage. No senior positions are undertaken for data roles in an organization. However urgency of sorted and confined data is required, which bootstraps the role of data engineering in the organizations. The senior-level management understands the importance of quantifiable datasets that help in making wise decision making in businesses. Data engineers will replace the role of data science as well hence we can say that data roles now come in front of the board-level seat. 

Dedicated Data Engineering Support for Every Team 

Data engineering has a big role in every team. This thing has now been understood by every organization. Data gives a quick insight into the business so that they can take decisions in the right direction. A data engineer collects and understands data in an organization, we can see a good example of this in the Sales Department. 

In a sale deparment, where the raw data of the customer has to be analyzed so that the sentiments of the customer can be understood. Data Engineer helps in making the data valuable by using the necessary metrics and helps the customer to stay on the platform. By identifying the correct data flow, the behavior of the customer can be identified, so that future directions can be taken easily due to which data loss can be prevented. That is why we can say that data engineers are very important for every organization.

More ‘Unicorns’ Will Be Solving Data Problems

Data Engineer is in demand in every industry. That is why it would not be wrong to say that there is a lot of demand for new unicorns. For those who want to make a career in the field of data engineer, it is necessary to learn the unique skillset. Data engineers ‘Unicorns’ do work like creating data models from pipelines, extracting insights from data, and analyzing data. It is very important for them to be proficient in complex skill sets. 

The list of unicorns has 2 best examples in the last 5 years: Databricks and Snowflakes. These two companies solved data storage problems. Another company name Segment works on collecting huge data. And this is not the end. In the coming years, new unicorns will enter into the industry of data. Therefore we can say that more Unicorns will be coming in to solve Data Problems in the future. 

Technology for Moving Data Will Become Commoditized

Data commoditization involves moving and securing the placement of data. And the significance of moving data has greatly improved after the arrival of cloud computing technology. At a time when data moving was an overhead for companies, data engineering was limited to dollar-billion organizations. 

But with the cloud computing technology the on-site data loading to server or remotely accessing, everything has turned out exhaling. The SaaS, software as a solution provider makes the flexible use of data under cost-effectiveness. Hence more than 50% of companies depend on cloud solutions for their data workloads which increases commoditization. So we can say that technology for moving data is becoming commoditized. 

Real-Time (and Near Real-time) Infrastructure Will Become Standard

However, at present the market seems to fluctuate with the presence of unuseful vendors across data customer platforms. The platforms are the unethical source to reach and track customer journeys but are only solutions for businesses for instance. Due to the limited presence of real-time infrastructures. 

Real-time infrastructures are in the beginning stage, so the organizations are focused on making their custom-made solutions but it requires huge hard work and cost. It will take 10 more years to enter into custom data infrastructures which will expand the role of real-time data pipelines to design products with the help of cloud platforms.

Data Engineer Career Trajectory and Future Roles

The data engineer career does not always begin from the ground level. Instead many business analysts and software engineers will turn out their careers as data engineers in the future marking the data engineering trends 2023. The intricacies and understanding of these jobs emerged with data engineering. Software engineers start off their careers as data engineers by developing advanced skill sets in data architecture and data science. 

The data engineer career trajectory crossed major breakthroughs in the entire role lifecycle. Therefore there has been immense scope in the future roles as a data engineer. 

The data engineer career roadmap would be to start up by launching a career in data engineering. At the beginning of the career, the engineer takes a small hands-on on the planning of smaller projects. Then as the career progress, the role of junior data engineer will be assigned to solve minor level bugs and errors in small projects. 

As the experience level increases the role becomes more proactive and advanced. The mid-level data engineer works more closely to handle major responsibilities with the project manager. A data engineer with over than 5 years of experience can fully manage the automation and data pipelines and develop deeper insight and outcomes for the company. 

The career hierarchy of a data engineer follows:

Data science engineer -> Data Architect -> Manager Data Engineering -> Chief Data Officer

Ready to Start Your Data Engineering Career?

Data Engineering has done a great roleplay in various business decision architecture and decision-making. Therefore, we conclude that data engineer future scope will be going to be more advanced and precise. As you begin your career as a data engineer, you deal with an alliance of integrated data sources and roleplay warehouse data lakes and siloes. Your scope could help to enlarge the vision of mid-sized and big companies.