Updated July 1, 2023
Introduction to Data Engineer Career Path
The data engineer is not a start-up role; mostly, the individual becomes a data engineer by starting his career as a business intelligence analyst or software engineer. As he grows up in his career, he moves into different flavors of data engineering like solution architect, data architect, and machine learning engineer. The companies like HP, Facebook, and Amazon hire data engineers to structure and optimize their businesses using data management. As per the increase in demand for data engineers, the posting becomes profitable with a six-digit salary.
What is a Data Engineer Career Path?
Data engineering is a wide discipline incorporating multiple labels, focusing on developing informative trusty infrastructures to check the consistent data flow in a data-driven environment. A person acts as an architect to clean the raw data gathered from various resources so that people can utilize it within his enterprise to make reliable decisions. He installed, tested, and maintained high-quality and confidential data to achieve organizational goals.
Step-by-Step Complete Roadmap in 2021
To become an effective data engineer in 2021, he must have a clear road map with well-defined knowledge and affirmative decision skills.
Pursue a Bachelor’s Degree in the Related Field where you want to become an Expert Data Engineer
Data engineers can do their bachelor’s degree in mathematics, science, information technology, or data-oriented field to have strong basic understanding skills. He can understand the basic programming language to get an entry-level job by pursuing software engineering.
Become a Master in the Related Skills
After pursuing the bachelor’s degree, he should fine-tune his skills in big data, databases, and programming languages. He can learn the basics of SQL and work on data queries. He can learn how to model the data, imply database architectures, practice with minimal data, build data pipelines, and work in data mining. After this, he can start to process the data in streams or batches. He can learn different big data tools like Hadoop, Kafka, etc., to list the workflows in the data ecosystem.
Go for Additional Courses and Certifications
It is good to keep an added professional certificate to boost his career in data engineering. He can opt for either Master’s degree in data engineering or can choose relevant technical skills in scripting, Kafka, Tableau, Java, automation, etc.
Become an Expert Programmer
The industry requires two main technologies one is Python and the other is Scala. He might go through concepts in these programming languages to develop standard software and should have hands-on experience. It can be done via online certifications, which are tool-oriented. So this can be added advantage and can be easily recognized at the time of the interview. People with strong knowledge of programming skills like Python, Java, C, and C++ are most welcomed by companies.
Working in and around cloud computing in this modern era is a mandate and critical. He must possess skills in cloud computing, such as cluster management, cloud storage, data management, computation, and so on. He can choose any popular cloud platform from AWS, Azure, and GCP.
Time to Upgrade Professionally
The standard way to advance professionally is by coping with recent trends and innovations in data science. Ensure that the professional updates themselves with new tools in data engineering and software launches. Work on multiple projects and develop a portfolio to display your technical knowledge to position yourself well in the standard data engineering enterprise.
To excel and sustain your company, apart from technical skills, there must be some added soft skills like collaboration, presentation, communications, and basic managerial skills.
Roles and Responsibilities
The major responsibilities and roles are an exploration of data analysis, extraction of data from a large pool of unfiltered raw content, cleaning and evaluation of data set, writing and preparing ETL logic, querying and mining data, binding data together, developing data stores, optimize data delivery, build a data pipeline to delegate to multiple servers, optimize data delivery, modeling and normalization of data, use the framework completely to serve the data.
Job Trend and Salary
The salary of data engineering is the one that drives people crazy in choosing it. The average salary of a data engineer falls from $65,000 to $135,000, and it varies according to professional certification, educational qualification, years of relevant experience, and additive skills. According to Glassdoor, the quoted annual salary for a data engineer is $102,864. From the report of Indeed, it is found that data engineers earn $129,415 per year. According to a recent survey, the average salary of a data engineer in the US ranges from ninety thousand dollars to one lakh twenty-six thousand one thirty-three dollars.
What Qualification is Required?
A data engineer’s basic qualification should be a bachelor’s degree; then, he should hold any additional certification and relevant experience in data engineering. Have strong programming skills, and learn cloud computing. He should work on real-time projects to gain experience in various portfolios, which will benefit his future employment.
What Skills are Required?
Data engineers possess key skills in programming languages like SQL, Java, and Python. Database skills, ETL tools like airflow, Hadoop, and Apache, cloud computing, and streaming include Apache Beam. He should know coding, relational and non-relational databases, ETL, data storage, scripting, automation, big data tools, and data security. Go for certification like IBM certified data engineer, Associate Big data engineer, Google Cloud certified professional, and Cloudera certified professional.
The path of the data engineer was to construct the raw data given to him, sort it, process it, and find the true part behind it. Only with that processed reliable data does he discuss with his organization to make any important decision that can make himself and his company grow.
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