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Big Data Engineer Job Description Template

Big Data Engineer Job Description Template

Monday, November 29th, 2021

Big Data Engineer Job Description Template

Looking for a Big Data Engineer? That’s why we’re here to assist you. The recruitment process seems very annoying to many people but if you look at it from a different perspective it can be so entertaining and creative. You’ll be well on your way to recruiting a new team member if you use VIVAHR’s FREE Big Data Engineer Job Description Template. It’s critical to have the right team on your side when it comes to candidate search. For this, we will be the ones taking care of you.

VIVAHR software is our plan for making the recruiting process more enjoyable for you. Follow our tips for finding candidates and adjust your credentials to each and every role you are looking for. This way, you’ll have a higher chance of finding the proper fit for the position.

What is a Big Data Engineer?

Big data engineers solve complex challenges in a strategic manner. They design and maintain data infrastructure and tools, which include gathering, storing, processing, and analyzing a variety of data and data systems. Big data engineers know how to work fast and correctly while analyzing large data sets with the best technologies available, and they know how to generate results.

Related Job Titles for Big Data Engineer

The Top Big Data Engineer Skills

Skill

Why it’s important

Machine Learning

Machine learning (ML) is an important tool for big data engineers because it helps them to quickly organize and handle massive volumes of data. In addition, because machine learning algorithms "learn" by analyzing data sets, big data is a component of their development. Engineers should be conversant with the process of creating machine learning algorithms. They must be able to develop them and employ algorithms in the data import process.

Hadoop

Hadoop is a set of open-source tools that can simultaneously handle enormous data volumes across thousands of servers and devices. Depending on the data and mode it operates in, it has variable degrees of the scale. Data engineers should be aware of the various modes and how they are used. They should also be aware of the technologies accessible to them and the situations in which Hadoop may be used.

Java

Because of its efficiency and object-oriented design, Java is one of the most extensively used coding languages. It's also one of the most widely used languages for developing data sorting algorithms and machine learning algorithms. This is why it is such an important talent for big data engineers. This is a language that engineers should be familiar with. They should also be conversant with Java machine learning libraries such as Java ML and know how to develop automated scripts.

Python

Python is a popular programming language because of its flexibility. Python has a large community and a large number of libraries. As a result, engineers should not only be familiar with Python and how to create tools with it but also be active in contributing to and using Python libraries.

Java

Because of its efficiency and object-oriented design, Java is one of the most extensively used coding languages. It's also one of the most widely used languages for developing data sorting algorithms and machine learning algorithms. This is why it is such an important talent for big data engineers. This is a language that engineers should be familiar with. They should also be conversant with Java machine learning libraries such as Java ML and know how to develop automated scripts.

Big Data Engineer Job Description Template (Free)

To create and manage our company’s big data solutions, we’re searching for a professional Big Data Engineer. You will be responsible for designing and implementing big data tools and frameworks, implementing ELT procedures, collaborating with development teams, building cloud platforms, and maintaining the production system in this position.

You should have an in-depth understanding of Hadoop technology, great project management abilities, and high-level problem-solving skills to succeed as a big data engineer. A top-notch big data engineer comprehends the company’s requirements and implements scalable data solutions to meet those requirements now and in the future.

Big Data Engineer Duties & Responsibilities:

  • Design and construct data applications for a number of teams and projects utilizing a variety of technologies and frameworks as needed and desired.
  • Read, extract, convert, stage, and load data into specified tools and frameworks.
  • Make scripts, scrape webpages, use APIs, and write SQL queries.
  • Integrate your work into our production systems by working directly with the technical team.
  • Transform unstructured data into an analysis-ready format.
  • Analyze the data that has been processed.
  • Monitor and change infrastructure to improve data performance.

Big Data Engineer Requirements:

  • 2–7 years of recent data engineering experience.
  • It is necessary to have a bachelor’s degree in computer science or a related field.
  • A proven track record of data management demonstrating faultless execution and meticulous attention to detail.
  • Strong statistical knowledge and expertise.
  • Experience programming, preferably in Python, Spark, Kafka, or Java, as well as a desire to learn new programming languages in order to accomplish goals and objectives.
  • It’s a plus if you know C, Perl, Javascript, or another programming language.
  • Data cleansing, wrangling, visualization, and reporting skills, as well as an awareness of how to employ the best, most efficient tools and apps to execute these tasks.
  • A readiness to attempt new approaches or solutions to tackle data mining problems, using industry best practices, data breakthroughs, and your own experience to complete the task.
  • Production support and troubleshooting experience.
Big Data Engineer Job Description Template
Big Data Engineer Job Description Template
Joshua F.
Redline Electric & Solar
Big Data Engineer Job Description Template

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Sample Interview Questions For Big Data Engineer

You can use these sample interview questions for Big Data Engineer once you’ve gathered all of the applications. These questions might ease the rest of your hiring journey.

Personal 

  1. Why did you pursue a degree in data engineering?
  2. Why are you interested in working for our company?
  3. Why should we recruit you as a member of our team?
  4. What distinguishes you from others?

Human Resources

  1. Tell us about one of your most difficult obstacles and how you overcome them.
  2. What kind of work atmosphere do you prefer?
  3. Do you feel at ease reporting to supervisors who are younger than you?
  4. Are you someone who considers themselves to be a leader?

Management

  1. How do you feel about changing your working plans?
  2. Do you like multitasking?
  3. How do you manage your time and deadlines?

Technical Skills and Knowledge

  1. Can you explain the many types of design schemas that are used in data modeling?
  2. Do you prefer to work with databases or pipelines?
  3. What has been the most difficult professional difficulty you’ve faced as a data engineer?
  4. How would you plan to design a new product as a data engineer?

 

What are the Educational Requirements For a Big Data Engineer?

Most big data engineers have a bachelor’s degree and others have a master’s degree, such as an online master’s in business data analytics. The additional years of education are critical for understanding the wide range of technical abilities required of a big data engineer.

How Much To Pay a Big Data Engineer When Hiring

Big data engineers usually earn between $76,000 to $168,500 per year, and their median annual salary is around $130,674. The hourly wages go from $39 to $81, and the median hourly pay is $63.

Percentile

10%

25%

50% (Median)

75%

90%

Hourly Wage

$39

$54

$63

$71

$81

Annual Wage

$76,000

$111,500

$130,674

$148,500

$168,500

Frequently asked questions about Big Data Engineer

 

What’s the difference between a data scientist and a data engineer? 

The primary distinction is the emphasis area. A data scientist is concerned with sophisticated mathematics and statistical analysis, whereas a data engineer is concerned with data creation infrastructure and architecture. To put it another way, the data scientist is concerned with answering questions, whereas the data engineer is concerned with supplying data.

What does the future hold for data engineers? 

According to IBM (2021), data engineers will see a 28 percent increase in job opportunities over the next three years. Finance, IT, insurance, and professional services will account for nearly 60% of all jobs.

What qualifications does a person need to work as a data engineer? 

You’ll require a strong understanding of programming languages and technologies like SQL, Cassandra, and Bigtable. You’ll need to know how to set up data-generating infrastructure and architecture. You should also be familiar with ETL and other data warehouse architecture.

Knowledge of Hadoop-based analytics is beneficial, and coding skills will give you an edge. Finally, familiarity with multiple operating systems such as UNIX and Linux is essential.

Several websites, such as Udemy and EdX, provide data engineering courses if you want to try them out. While you won’t generally be able to get certified this way, it is a wonderful method to put your skills to the test.

Similar Job Descriptions as Big Data Engineer