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Data Engineer Job Description Template

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  • Reconciling billing accounts to the general ledger
  • Interfacing with the accounts receivable, credit/collections, and client purchasing departments
  • Ensuring the accuracy of invoicing for the company and its customers
Group 69435

Job Brief :

We are looking for a Data Engineer for our organization. The Candidate is required to provide aid to the Data Scientists of the organization. Your main duty will be to transform data into a form that extraction and analysis of data are made easy. To do so you will have to build an infrastructure that supports all the required activities. You will also have to maintain the structures and test them to ensure that it’s usability.

You might also have to collaborate with the co-members within the department to make sure your work approach is in line with organizational goals.

To be a successful Data Engineer good interpersonal skills, analytical skills, problem-solving ability are the most important skills.

Responsibilities :

  • Collaborate and cooperate with the team members to explain each task clearly to everybody.
  • Gather all the complex data sets keeping in mind the functional and non-functional requirements of the organization’s business.
  • Work towards automatizing all the manual processes in the department.
  • Identify areas of improvement in the internal process, design the improvement processes and ensure its implementation.
  • Build infrastructure that supports big data access as well as analysis.
  • Perform testing of structures to make sure they are ready for final use.
  • Produce raw data for the Data Scientists to perform manipulations to achieve the company’s goals.
  • Do error detection and correction in the work processes.
  • Make sure your work is backed up and readily available for the use of colleagues with a simple extraction method from various data sources.
  • Take care of the security of the data across the boundaries.
  • Develop analytical tools to have an insight into operational efficiency, customer acquisition, and other essential information for business improvement.
  • Be well-versed with the industrial standards.
  • Stay updated with the technological growth in the industry and use it wisely to make improvements in your work.

Requirements :

  • Bachelor’s degree in Computer Engineering, Data Engineering, or any other related course.
  • Proven experience in Data Engineering or in other relevant roles.
  • Well-versed with programming languages like C++, Java, Python, R language, etc.
  • Outstanding analytical ability.
  • Excellent problem-solving skills and troubleshooting abilities.
  • Good verbal and written communication skills.

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Frequently asked questions

Salaries depend on location and years of experience involved. But on average a Data Engineer on an entry-level earn about Rs.790K per year.

Posting this job description on various job boards such as AdzunaZipRecruiterindeed and CareerJet can help get you better reach of the candidates. Using an ATS like Recooty can help save you a great deal of manual work! This allows you to post jobs to more than 20+ job sites from here: Recooty.

Top industries that hire Data Engineers are:

◦ Retail industry: The retail industry needs to analyze and understand correctly what are their customer’s needs and requirements. As the competition in the market is very high, if any company misses on this then they will probably lag behind in the competition. Data engineering helps retailers in getting the insight they need to keep the customers satisfied and be at the top in the market.

◦ Medical industry: Medical industry is always trying to improve health in a variety of ways. Data engineering is a key for them for this work. This data engineering in signs provides essential information to the physicians on patient’s well-being so that they can extract better actionable data from it.

◦ Banking and finance: Earlier, the banking industry was not the one that uses technology a lot. However, now the picture has completely changed. Bankers are beginning to use technology increasingly to drive decision-making. The banks have started using predictive analytics and language processing to create a virtual assistant that helps customers view information and transaction histories. These virtual assistants are trying to get smarter with every transaction.

◦ Transportation industries: There is a need for the people in this industry to reach a particular destination or transport goods on time. Data engineering is used to increase the chances of successful on-time deliveries. In some places, it is also used to Map the journey of the customers, manage difficult circumstances, and for providing personalized transport details.

◦ Media and entertainment industry: nowadays people look for Rich media as and when they need it on a variety of devices. For the analysis collection and utilization of this consumer insight the use of data engineering very important.

The top skills for a Data Engineer are:


It is a highly valued skill and is required majorly in this profile. Every employer looks for a candidate who has at least a basic understanding of the programming languages mostly use in the company stop. Programming languages that are most in-demand today are Python, R language, C/C++, Ruby Pearl, Matlab, etc.

Database management :

To excel in this profile every candidate should have a deep understanding of database management. Each candidate should have good knowledge of SQL as it is the most widely used language in database management. Other than SQL there are other database solutions as well. You might study that in order to get a better hold of the company’s database.

Analytical skills:

In this profile, you have to deal with a large amount of data and derive valuable insights from it. Every employer therefore what is the candidates to have a good understanding of analytical software.

Critical thinking abilities:

Data into the news I suppose to handle the issues that arise in between and come up with effective solutions. Sometimes you might get solutions with the help of research. But for the other times, you have to develop a solution that doesn’t exist yet. So the ability to think critically is important.

Familiarity with machine learning:

Machine learning is a major part of the data scientist profile. It is helpful for the finance bank. A basic understanding of ML helps you in understanding how to use a particular type of data. Knowledge of data modeling and statistical analysis will help you to create solutions that can be used by fellow team members. It will make you outshine in your department amongst your colleagues.

Good verbal and written communication skills:

In this profile, candidates have to collaborate with colleagues as well as higher officials of the organization. You have to attend meetings and interact with seniors as well as juniors within the department. Sometimes you have to explain certain technical concepts to those who do not have technical expertise. In order to be able to share your findings and suggestions with everybody communication skills are important.

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