Today’s world is called a world of digital data, and we are surrounded by it in day-to-day life. It is witnessed that most of the companies have completed the digital transformation, which creates a huge volume of new types of data and much more complicated data at a higher frequency. So here comes the real importance of data engineering. Basically, data engineering is needed to make sense of data. Here data engineers ensure the quality, availability, and security of the data. They are expected to build the necessary infrastructure and data pipelines to prepare data for analysis.
The known thing about data engineering is that this field is related to the analysis and processes and storage of data from other (internal and external) sources. So the role of data engineers is to process those data sets and convert them into clean and filtered data used in further processes such as business analytics, data visualization, data science solutions, etc. Therefore, there is a huge demand for data engineers to understand, handle, and effectively perform data tasks wisely. To provide skilled data engineers and data experts, many companies are organizing Data Engineering Bootcamp and training courses to help professionals start a dynamic career in this domain. Here we will discuss the job role of data engineers and their basic roles and responsibilities in any organization.
Embed Youtube Video URL here: https://www.youtube.com/embed/W1ibmcDND64
What is a Data Engineer?
A Data Engineer is an IT professional who prepares data for operational and analytical purposes. Data Engineers are also known as Software engineers typically responsible for creating data pipelines to bring together information/data from different sources and systems. They are expected to make data easy to access and optimize their organization’s big data ecosystem. Their main job is to gather, integrate, consolidate and cleanse data and structure it for further use in analytics processes or applications. They are also responsible for finding trends, patterns, and insights in data sets. They develop algorithms to help make raw data more useful to the companies. For such a tough job role, data engineers require a significant set of technical skills that involve deep knowledge of multiple programming languages, including SQL database design.
The work of a data engineer varies on the type and size of an organization and the amount of data produced by them. The bigger the company, the more complex the level of analytics architecture, and the more the amount of data the engineer will be responsible for. So they are considered vital members of any enterprise data analytics team. Data engineers manage, optimize, monitor, and oversee data retrieval, distribution, and storage throughout the organization. They work along with data science teams to improve data transparency and enable businesses to make more trustworthy business decisions.
For a successful career, a Data engineer must understand how to optimize data retrieval and how to create reports, dashboards, and other visualization for stakeholders and other team members. We can understand more about data engineers with the following mentioned roles.
The Data Engineer Role
Data engineer’s main job is to collect and finally prepare the data for use by data analysts and scientists. So they are categorized into the following roles.
- Data Engineers as Generalists- As a generalist, data engineers typically work on small terms, collect data end-to-end, intake, and process it. These engineers may have more skills and knowledge than software engineers but less than system architects. A data scientist can also be fit in a generalist role if he wants to switch to a data engineer. A good example for a data engineer generalist is that he might undertake a small, food-delivery service to create a dashboard that displays the number of deliveries made each day for the past month and predict the delivery volume for the upcoming months.
- Pipeline-Centric Engineers- These engineers work on a midsize data analytics team and difficult data science projects across distributed systems. Medium and big-size organizations are more likely to need pipeline-centric engineers. For example, a regional food delivery company might undertake a pipeline-centric project that can build a tool for data analysts and scientists to search metadata for relevant information about deliveries so they can make many meaningful business decisions regarding distance and time taken for food deliveries.
- Database-Centric Engineers- These types of data engineers are demanded by large size companies where data is distributed across many databases. They are tasked with implementing, populating, and maintaining analytics databases. Database-centric engineers work with pipelines and tune databases for analysis and build table schemes via extract, transform, and load (ETL) methods. For example, these engineers can work with large, multistate, or national food delivery services where they design an analytics database. They can also write the code to get data from where it is gathered in the main application database into the analytics database.
Data Engineer’s Responsibilities
We can better understand what a data engineer does with the following mentioned details. Some of the common responsibilities of a Data Engineer are:
- Developing, creating, testing, and maintaining data architectures.
- Collect data from the right source, then process, store and optimize the datasets.
- Data acquisition.
- Align architecture according to business requirements.
- Develop data set processes, and improve data reliability, quality, and efficiency.
- Use programming languages, skills, and tools effectively for cleaning data
- Use large datasets to solve business problems.
- Create models and identify patterns and trends.
- Automate data tasks
- Improve technical and soft skills.
- Conduct research to address any issue that can arise while tackling a business problem.
- Deploy sophisticated analytics programs, machine learning, and statistical methods.
- Prepare data for prescriptive and predictive modeling.
- Identify hidden insights and patterns in data.
- Prepare reports and dashboards.
- Deliver updates to stakeholders based on analytics.
With a large set of roles and responsibilities, A data engineer can earn an average salary of $137,776 per year according to Glassdoor. Their salaries vary depending on skills, company size, location, and experience, So starting a career as a Data Engineer sounds quite attractive and worth investing your precious time, money, and efforts. Hurry up to become one.