Here are 7 Important Data Engineer Skills for Aspiring Professionals
Arvind Shetty of IBM Analytics once remarked that every discussion about changes in technology, business, and society begins with data. He was not wrong. He went on to conclude that “data is becoming a new natural resource”. It is no secret that information is king in today’s data-driven world. Data in and of itself, however, is useless. This is where organizations need a data engineer skill set to transform information into insights. This demand is borne out by the fact that the Indian market for data engineering will be worth $124.7 billion in 2028. So, which data engineer skills are relevant in today’s market? This is a valid question because there are several valuable skills for data engineers that give them the tools to tackle all things data.
So, let’s dive deep into the essential data engineer skills, their role in building data pipelines, and why they may be indispensable to potential employers.
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What is Data Engineering?
Data engineering is the foundation that enables you to extract information from raw data. Critical activities such as collecting, storing, and prepping data are part of a data engineer skill set.
For example, think of data engineers as librarians building systems to categorize books in a library. Similarly, data, like books, comes in all sorts of languages and formats. The data engineer skills help translate data into a common language and arrange it in an accessible way.
The construction of data pipelines is among the crucial skills for data engineers. These automated systems collect data from various sources, clean and convert it, and then load it into data warehouses or lakes for analysis.
Data engineers decide how and where to store large volumes of data efficiently by evaluating factors such as scalability, security, and cost. Lastly, they must ensure that the data is accurate, complete, and consistent across the board.
The data engineer skills required by companies are quite elaborate, increasing the number of data engineers earning between ₹6 and ₹10 lakh from 23% in 2023 to 32.4% in 2024. In fact, there are more than 10,593 job openings for data engineers across online job portals.
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Core Skills
“If you want people to make the right decisions with data, you have to get in their head in a way they understand,” says MIT Sloan senior lecturer Miro Kazakoff. This is why one needs a strong set of data engineer skills. Let’s see what they include:
1. Programming Languages
Python is among the data engineer skills required to succeed at the top level. The language is often used for data manipulation and automation. Furthermore, SQL is useful for querying databases and manipulating relational data, whereas Java/Scala is used in big data technologies like Apache Spark.
2. Database Knowledge
It is important to understand relational (SQL) and non-relational (NoSQL) databases to facilitate data storage and retrieval. For instance, data engineers need to be fluent in relational databases such as MySQL, PostgreSQL, SQL Server, and Oracle. They need to be familiar with NoSQL Databases like MongoDB, HBase, Cassandra, and DynamoDB.
3. Big Data Technologies
The role of frameworks such as Hadoop, Spark, and Kafka is critical in handling massive and complex datasets. They feature among the most coveted data engineer skills. Professionals must know their way around the Hadoop Ecosystem. Apache Spark helps with large-scale data processing, whereas Kafka comes in handy for real-time data streaming.
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4. ETL/ELT Processes
Extract, Transact, Load (ETL) and Extract, Load, Transfer (ELT) are two fundamental software approaches to building data pipelines. These automated systems move data from various sources to a central location like a data lake or warehouse for analysis. They differ in the order and location of the data’s transformation. Here’s how:
A. In ETL, data is transformed before it is loaded into the target system. Major tasks like data cleaning, formatting, combining data from different sources, and applying business logic typically occur in a separate staging area.
B. On the other hand, in ELT, the data is added to the target system in its raw state. The transformation process takes place with the help of its processing power. This approach is common with data lakes, which are designed to handle large sets of raw data.
5. Cloud Computing
The significance of cloud platforms for data storage, processing, and scalability remains undisputed. Most businesses rely on platforms such as AWS, Microsoft Azure, and Google to meet their IT needs. It is, thus, important to have a working knowledge of these platforms as a data engineer.
6. Data Governance and Security
Every organization wants data to be accurate because inaccurate data yields wayward results. Data engineers must know how to deliver consistent and reliable data. They should leverage tools such as encryption, data masking, and access controls to enhance security. It is necessary to comply with the relevant regulations.
7. Soft Skills
The skills required for data engineers are not limited to technical specifications. A data engineer requires many soft skills to succeed in the role. Here are some of the more important ones:
A. Problem-Solving
Data engineers encounter numerous challenges while dealing with data. They need to hone their analytical and problem-solving skills if they are to find solutions.
B. Communication
Data engineers must know how to clearly explain technical concepts to both technical and non-technical audiences if they are to thrive in a firm.
C. Collaboration
Data engineering projects often involve collaboration with data scientists, analysts, and other engineers. The ability to work effectively within a team is crucial.
D. Critical Thinking
Critical thinking is a major component of data engineer skills. The skill helps to stay updated on new technologies, identify areas for improvement, and develop innovative solutions to streamline processes.
Start Your Data Engineering Journey
The skills required for data engineers can be honed with the help of a few easy tips. Aspiring individuals can learn programming and database languages such as Python, SQL, etc., using tutorials available online.
Moreover, it is prudent to explore frameworks like Apache Hadoop, Spark, and Kafka. There is a need to master cloud platforms and get a relevant certification to validate your skills. Google Cloud, Azure, and AWS are some popular names.
Platforms like Emeritus offer many online courses, catering to everyone from beginners to veterans. There are boot camps that provide intensive training over weeks or months to equip you with data engineering skills.
Lastly, it is crucial to have a portfolio that showcases your skills, passion, and initiative. Therefore, it is handy to experiment by building a data pipeline or developing a web application. Contribute to open-source projects to gain practical experience and network with developers.
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In conclusion, the use of data is going to define the future era. Every company is going to be on the lookout for professionals who can help navigate their firm through this future. Emeritus offers data science courses designed by industry experts to equip you with the skills that are in high demand. These courses cover everything from data analysis and machine learning to big data technologies and data visualization. Enroll in one of these courses and give your career the boost it needs.
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