Effective and timely decision making can result in great savings and can take the organization to new heights. The reverse is equally true, one wrong decision can cost millions to organizations. In today’s world, the decision-making process is the backbone of good management, however, decisions must always be backed by data. Without the data, one cannot make timely informed decisions. Therefore data is very important for any organization.
With rapid data generation, it is nearly impossible for anyone to make quick inferences from raw data. The organization needs tools, technology, and resources to reduce raw data and summarise it before arriving at any decision. As the amount of data generation is growing exponentially, organizations are spending a huge amount for processing data and developing infrastructures for data analysis inhouse. Consequently, Big data analytics and data specialist roles are becoming valuable departments in all organizations.
Data specialists with dedicated teams have to work on new tools and technologies constantly and regularly upgrade themselves to keep up with the data generation pace. Regularly new tools and methods are being developed. This has created a bucket of opportunities for a good and stable career.
In this article, we will try and learn more about data engineering, its roles, and responsibilities, skills required, salary, and demands of .
Who is a Data Engineer?
Data specialists usually consist of data engineers, data scientists, data analysts, software developers, and database architects. Some or all of them work together as a dedicated team in an organization to transform data for meaningful inferences. Each one of them would be working on specific tasks to accomplish the overall objective of data transformation, However, some overlap of responsibility might happen based on the type of organization. In this article, we are focusing on data engineering roles and responsibilities. Let us look at what a data engineer is and what he is expected to do in more detail.
A is one who develops infrastructure and a data pipeline to transform the data in a readily available format. Data engineers ensure data availability to other team members for any further analysis. In detail, data engineers are involved in preparing, cleaning, filtering, modifying data from various sources by writing moderate to difficult scripts.
Roles and Responsibilities
Core responsibilities of data engineers usually depend on the work scope of the project. If a project is started from scratch, data engineers will have more responsibilities compared to an ongoing project. Overall at higher-level, data engineers have the following set of responsibility:
- The primary job of a data engineer is to collect data from all sources, in all sorts of formats, integrate, manipulate, save, and utilize it when required. In short, they design a robust data pipeline to help other team members.
- Design and develop data flow architecture.
- Work on optimization or enhancement of existing data flow architecture.
- Optimize data pipelines to minimize errors in raw data.
- Design or maintenance of databases.
- Data mining, filtering, and support in data modeling.
- Create or support on dashboard creation commonly known as dynamic visualizations or reporting.
The roles and responsibilities of a Data Engineer sometimes overlap with that of data scientists or data analysts. It may be due to the absence of clarity in responsibility in some organizations or due to limited resources. You might end up doing some work specifically done by data scientists.
Some basic skills that data engineers should have in order to secure a successful career are:
- Experience with tools like Azkaban, Luigi, and Airflow. The flow of data is key to the data engineer role, an excellent understanding of data pipelines are a must for any data engineer.
- In order to provide usable data to the team, data engineers should have sound knowledge of incoming data type, format, and data acquisition systems.
- Data mining is very important to only extract data that is usable and improve upon the performance of the system.
- Sound scripting knowledge for writing queries for data processing and automation.
- A sound understanding of SQL is recommended for a good data engineer. In addition, skills related to NoSQL databases and tools such as Apache hive, Impala is highly recommended.
- Hands-on experience in the Big data environment and in-depth understanding of tools like Hadoop, Spark, MapReduce, Kafka is good to have.
- Data warehousing, storage are essential skills.
- In order to connect to various partners, good communication skill is a must to have for any data engineer.
In addition, the following skills are preferred
- As data engineers closely work with Data scientists and analysts, basic awareness of statistical tools would be good to have skills.
- Artificial intelligence and machine learning are the future for any data specialist role, so a basic understanding of all both should be acquired.
Organizations seeking data engineers
Almost all the organizations are seeking good data specialists for data analysis which can help them with their research on new technologies. Some of the prominent names include Google, Microsoft, Apple, Facebook, Daimler, Audi, Twitter, IBM, Boeing, Amazon, Accenture.
You can work as a full time professional or part-time or as a freelancer. Moreover, work from home is a viable option in the data analysis field which can be helpful for some candidates.
Salary and Demand
Almost all companies in all sectors require data specialists to collect, clean, and reduce data to help management and other functions to make effective and timely decisions. The demand for Data specialist roles has grown rapidly in the fast few years. As demand is growing due to an increase in data and evolving technology in data engineering. It offers a fair amount of stability in one’s career. As job security and career, stability is one of the key concerns in recent times due to the situation created by Artificial intelligence and pandemics.
Data specialist is also one of the higher-paying jobs as it is technology-driven, requires good understanding and lack of skilled professionals in the field. According to Payscale, the average salary of a Data Engineer in the United States is per year.
With the rapid generation of data in all sectors, the Data engineer field is ever-growing and quite lucrative. Many opportunities are created every day that one wouldn’t want to miss. One can be a successful data engineer if he is interested in the data analytics field in the comfort of his home. There are many courses available online that can help to become a successful data engineer. The courses are often prepared by industry experts having extensive knowledge and experience in the data engineering field. Courses are curated based on experience levels and knowhow of candidates. One should opt for an online course suited to their needs as a good understanding of concepts and tools are very important to learn in the data analytics field for a successful career. So all in all with a carefully selected training course once can start his journey for the data engineering field. So, without wasting your precious time, enroll for a course now, and embark on the opportunity!