The current market is data-driven, and with the emergence of newer trends and the need to outsmart the competition, businesses are increasingly relying on data engineering and analysis.
The demand curve for data engineers has risen steeply in recent years. Research says it was the fastest-growing tech occupation in 2020 and will experience a 50% year-over-year growth. Its estimated CAGR is to be 21% during 2018-2028. This increasing demand creates fierce competition between organisations to attract and retain top talents.
Consequently, a compelling data engineer job description can help you recruit the best. We will share details on job description creation in this article.
What Does a Data Engineer Job Profile Look Like?
Data Engineers are responsible for building systems that can collect, manage, and transform raw data into usable information for organisations. The main target is to ensure data accessibility for making data-based decisions and optimising business performance.
They also help develop and maintain datasets and architectures that allow you to extract data and transform them for predictive or prescriptive modelling.
Your data engineer job description must start with a brief of what you expect from the candidates and their day-to-day duties. Additionally, you must briefly introduce your company and its goals, skills required for the open position, employee benefits and salary packages, and contact information.
Data Engineer Requirements
Now that you are developing a data engineer job description, you must state their educational requirements. According to research, most candidates applying for a job don’t even meet the qualification requirements. Therefore, you must state your requirements explicitly so that only the most eligible candidates can apply.
Educational Requirements
Usually, a candidate applying for data engineering jobs needs to have a graduation degree in data engineering, computer science, or a related field.
Additionally, these candidates must be fluent in using multiple tools and the latest big data technologies. You must equally focus on a data engineer’s technical and soft skills to make the right choice.
Some of these are:
- Strong grasp of advanced SQL and relational database management
- Expertise in object-oriented programming languages like Python and Scala
- Work with distributed computing frameworks like Spark or Hadoop
- Understanding of data pipelines and workflow management tools
- Experience with cloud-based solutions
- Well-versed in different operating systems like Unix, Linux, Solaris and Windows
- Basic Machine Learning knowledge
Besides tech skills, an applicant must have strong project management and organisational skills to become a data engineer. Additionally, verify their problem-solving, communication, and teamwork capabilities.
Experience
Though most companies prefer hiring experienced data engineers, you may not get huge options for the same. Data engineering has been on the trend for a few years, so finding experts with 5+ years of experience may be tough.
However, you can look out for candidates with a minimum of 1-2 years of experience and knowledge of using multiple software and tools. It includes expert usage of databases, pipeline tools, stream processing systems, and object-oriented scripting languages.
Data Engineer Roles and Responsibilities
Your data engineer description may include the roles you are hiring for and the candidate’s responsibilities. This helps candidates understand their eligibility before applying for your vacancy.
Additionally, most recruiters today use ATS software to filter resumes. Therefore, the chances of losing high-quality talents increase if you don’t create the ideal candidate profile properly mentioning roles and responsibilities.
However, before you start crafting a data engineer job description, let us understand their main roles and responsibilities.
Roles of Data Engineer
There are three main data engineering roles that candidates apply for in an organisation.
Generalist Data Engineers
These candidates usually need to work on small teams and far from end-to-end data collection. A generalist data engineer usually has more knowledge and skills than other professionals in the same domain. However, they can have less familiarity with the system architecture.
Pipeline-Centric Data Engineers
Pipeline-centric data engineers are mainly hired in mid-sized and larger companies. These individuals work across distributed systems on complicated data science assignments to collect data.
Database-Centric Data Engineers
Large establishments hire database-centric data engineers to work on data distributed across multiple databases. They are responsible for working closely with data scientists in multiple data warehouses and creating table schemas.
Data Engineer Duties
We have listed a few data engineer duties you can add to your job descriptions.
- Collecting, analysing, and organising raw data
- Help build data systems and pipelines to clean, transform, and aggregate data from different sources.
- Evaluating your business needs and objectives and interpreting trains and patterns
- Work with the data science team to build complex algorithms and provide unique data insights.
- Making iterative improvements to backend systems by using agile software development processes
- Developing business intelligence reports for your company advisors
- Supporting the development of data streaming systems
- Creating new data validation methods and data analysis tools
- Ensuring compliance with data regulation and security policies
What is the Data Engineer Career Prospect?
Most individuals today look for career growth while applying to a company. Therefore, you can include data engineer career prospects in your job description to ensure you value their growth and development.
However, before that, you must understand the career path of a data engineer, which makes hiring the right person for the right role easy.
Entry-Level Data Engineer
If you are hiring for entry-level data engineers, you must look for individuals with a graduation degree in computer science or related fields. These people must know programming languages, databases, and Big Data technologies. They usually work on small data engineering projects under the guidance of mentors or experienced data engineers.
Junior Data Engineer
These individuals usually have little experience in data engineering and expertise in one or more programming languages, databases, and Big Data technologies. They can work on more complex projects than entry-level engineers and can design and implement data solutions.
Senior Data Engineer
You can hire a senior data engineer in your company as they have years of experience in the domain and developed expertise in multiple languages, databases, and technologies. They can lead your projects and work with other data engineers to implement complex solutions.
Lead Data Engineer
These experts usually have extensive experience in the data engineering domain and have previously demonstrated leadership skills in other companies. They can oversee your team of data engineers and take over the responsibility for implementing data solutions across your company.
Data Architect
A data architect focuses on designing and implementing the data architecture of your company that aligns with your business goals. They will collaboratively work with business stakeholders and data engineers to create data solutions that are scalable, reliable, and secure.
Data Infrastructure Manager
These individuals can manage your organisation’s data infrastructure, including your data warehouses, databases, and Big Data technologies. They can handle a team of data engineers and work collaboratively with other IT departments to generate data solutions integrated with other business systems.
Chief Data Officer
The chief data officer holds the most senior executive responsibility in an organisation. They manage your data strategy and ensure it is effectively used to support your business goals. These professionals oversee your organisation’s data engineering, analytics, and governance functions.
What is the Average Data Engineer Salary?
While creating a data engineer job description, you must know their average salary to ensure you pay workers fairly. We have listed the salary estimates of data engineers in the GCC.
- Sultanate of Oman: The average annual salary of a data engineer in Oman is OMR 8000.
- Republic of Iraq: Iraq pays their data engineers IQD 43,278,368 yearly on average.
- Kingdom of Bahrain: Data engineers in Bahrain receive 17,620 BHD per year on average.
- United Arab Emirates: Data engineers in Dubai receive AED 120,121 on average.
How Does 6 Pence Help you in Creating a Data Engineer Job Description?
You can look into multiple online templates if you struggle to create a compelling data engineer job description.
6 Pence has been helping top organisations across Dubai, Oman, Bahrain, and Iraq hire qualified individuals for their open positions. We have a vast repository of qualified talents and experienced recruiters, allowing us to find you the best-fit employee.
If you are looking to work as a data engineer in the GCC, apply for jobs through our platform. Check our careers page on the website or follow our social media pages to stay updated!
Also Read: 8 Easy Steps To Improve Employee Productivity in the Workplace
Frequently Asked Questions
What are data engineering skills?
The common data engineering skills include knowledge of programming languages, statistics, analytical skills, understanding of Big Data technology, knowledge of databases and multiple operating systems, etc.
What are the requirements for a data engineer?
A data engineer must graduate in data engineering, computer science, or related fields. They must have expertise in using multiple programming languages, SQL, distributed computing frameworks, data pipelines and workflow management tools, operating systems, etc.
What is the difference between a data analyst and a data engineer?
The main difference between data analysts and data engineers is their expertise and skill sets. While a data analyst focuses on data analysis, a data engineer works on data infrastructure.
