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Data Engineer
Data Engineer
Data engineers design and build systems to collect, process, store, and analyze large amounts of data. They work closely with data scientists, analysts, and other stakeholders to ensure that the data is reliable, accurate, and accessible. Data engineers typically have strong programming and database skills, a deep understanding of data warehousing and processing techniques, and experience with cloud computing platforms.
Salary Range
with 5 years of experience
💵
$110K - $150K
per year
Benefits and Perks
Explore the typical benefits you might find in this field
🎖
Long Service Rewards
📈
Professional Development
💻
Supplied Technology
🧕
Inclusive Workspace
🏘
Work from Home
Length of Training
How many years of training are required to be a Data Engineer?
⏳
2
years of training
What's it like to be a Data Engineer?
Data engineers work in a fast-paced, dynamic environment where they are constantly learning and adapting to new technologies. They need to be able to think critically and solve problems efficiently, and they must be able to communicate effectively with both technical and non-technical stakeholders.
Key Aspects of the Job
- Designing and developing data pipelines
- Building and maintaining data仓库s
- Developing data quality procedures
- Working with various programming languages and tools
How to enter the job?
There are a number of different paths that one can take to become a Data Engineer. Some people start by earning a bachelor's degree in computer science, engineering, or a related field, while others may come from a more business-oriented background and earn a master's degree in data analytics or business intelligence.
Educational Requirements
- A bachelor's degree in computer science, engineering, or a related field is typically required.
- Experience with programming languages and tools such as Python, SQL, Hadoop, Spark, and cloud computing platforms such as AWS or Azure.
- Strong problem-solving and analytical skills.
Task & Duties
Data engineers are responsible for a wide range of tasks, including designing and building data pipelines, building and maintaining data仓库s, developing data quality procedures, and working with various programming languages and tools. They may also be involved in working with data scientists and analysts to define data requirements and ensure that the data is available in a timely and efficient manner.
Primary Duties
- Designing and developing data pipelines that collect, transform, and load data from various sources.
- Building and maintaining data仓库s that store and organize large amounts of data.
- Developing data quality procedures to ensure that the data is accurate, complete, and consistent.
- Working with various programming languages and tools, such as Python, SQL, Hadoop, Spark, and cloud computing platforms like AWS or Azure.
- Collaborating with data scientists and analysts to define data requirements and ensure that the data is available in a timely and efficient manner.
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