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Last updated on 2024年9月13日

You're starting a career in Data Engineering. How crucial is hands-on experience for your success?

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Embarking on a data engineering career is an exciting journey into a field that's crucial for managing and interpreting the vast amounts of data generated today. Hands-on experience in this field isn't just beneficial; it's a cornerstone for your success. Data engineering requires a practical understanding of systems that store, retrieve, and process data. As you delve into this career, you'll find that real-world experience with databases, data pipelines, and large-scale processing systems will not only bolster your resume but also give you the confidence and skills needed to tackle complex data challenges.

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Luciano Vasconcelos Filho

Engenheiro de dados e professor da Jornada

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Nikhitha Joy

Data Science and AI Engineer at Intelance | Top Data Science and Machine Learning Voice | Healthcare Tech Enthusiast |…
Bruno Andrade

Tech Lead | Data Engineering | AWS Certified Solutions Architect

1 Core Skills

The core skills for a data engineer include proficiency in programming languages such as Python or Java , understanding of database management systems (DBMS) like MySQL or PostgreSQL, and experience with big data tools like Hadoop or Spark . Gaining hands-on experience with these technologies through projects or internships allows you to understand their practical applications and limitations. This practical knowledge is crucial when designing and optimizing data systems for efficiency and scalability in a real-world setting.

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Luciano Vasconcelos Filho

Engenheiro de dados e professor da Jornada
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Experiência prática é fundamental, blablabla (você já sabe disso), mas é difícil de ter sem estar no mercado. Vou dar uma dica diferente que é simular um projeto como se fosse um desafio real. Pegue um projeto de uma aula no YouTube ou da Jornada de Dados, e assista aos primeiros 20 minutos e pause. N?o assista a aula toda. Assista o come?o e pause. Entenda o problema e tente resolver em uma semana sem voltar ao vídeo. SE VIRA! Quando terminar, compare sua solu??o com a da aula. Isso for?a você a sair da zona de conforto e ainda te dá um code review para melhorar seu código - comparando com o da aula. é uma forma de ganhar prática mesmo fora do mercado e de passar pelo “sofrimento” de n?o saber exatamente o que fazer.

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Nikhitha Joy

Data Science and AI Engineer at Intelance | Top Data Science and Machine Learning Voice | Healthcare Tech Enthusiast | BTech in Artificial Intelligence and Data Science
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Gaining hands-on experience is pivotal in data engineering as it bridges the gap between theoretical knowledge and practical application. While understanding programming languages, database management systems, and big data tools is essential, actively working with these technologies on real projects or through internships helps solidify your skills. This experience allows you to navigate the complexities of designing, building, and optimizing data systems in real-world scenarios. By engaging in hands-on work, you not only deepen your understanding but also develop the problem-solving skills necessary to succeed in the dynamic environment of data engineering.

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Monish Bandapalli
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Hands-on experience is absolutely crucial in a Data Engineering career. While theoretical knowledge helps you understand concepts, working directly with tools like SQL, Python, ETL pipelines, cloud platforms, and big data technologies gives you the practical skills needed to solve real-world problems. It sharpens your ability to handle complex data systems and builds confidence in designing and optimizing data workflows. You can’t fully grasp the challenges and nuances of data engineering without applying what you learn in real projects.

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Bruno Andrade

Tech Lead | Data Engineering | AWS Certified Solutions Architect
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Solid experience around Extract, Transform and Load will build the foundation for every data pipeline you will ever build. Once the basics are clear and simple ETL applications are easy to understand, advanced skills such as distributed computing can be worked on.

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2 Learning Curve

The learning curve in data engineering can be steep, but hands-on experience helps flatten it. Engaging with real datasets and infrastructure allows you to apply theoretical knowledge to practical problems. For example, by working with Extract, Transform, Load (ETL) processes, you gain insights into how data moves within an organization and learn how to troubleshoot issues that arise during these operations. This kind of experience is invaluable and can't be fully replicated in a classroom.

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3 Tool Mastery

Mastering the tools of the trade is essential for any data engineer. This includes everything from SQL for database manipulation to cloud services like AWS or Azure for scalable data storage and processing solutions. Getting hands-on experience with these tools not only helps you understand their nuances but also teaches you how to integrate them effectively to build robust data pipelines and storage solutions.

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Bruno Andrade

Tech Lead | Data Engineering | AWS Certified Solutions Architect
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Always check for certification programs, there are many opportunities for you to get a free certification voucher after participating in official training from AWS, Azure, GCP, etc., which can increase your knowledge with the tool while boosting your resume.

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4 Project Experience

Working on actual data engineering projects is one of the best ways to gain experience. These projects can range from setting up databases to creating data processing pipelines. Through this, you'll encounter challenges such as ensuring data quality and consistency, which are common in the industry. Project work also teaches you about version control systems like Git, which is essential for collaborating with other professionals in the field.

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5 Industry Knowledge

Understanding industry-specific data needs is another area where hands-on experience is invaluable. Different sectors have unique data challenges and regulations, such as HIPAA for healthcare data or GDPR for user data in Europe. By working on projects within a particular industry, you gain a deeper understanding of these requirements and learn how to build compliant and effective data solutions.

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6 Networking Value

Finally, hands-on experience provides networking opportunities with other professionals in the field. Collaborating on projects or contributing to open-source initiatives can connect you with mentors and peers. These connections can lead to job opportunities and partnerships that are beneficial throughout your career. Engaging with the community also keeps you updated on the latest trends and best practices in data engineering.

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You're starting a career in Data Engineering. How crucial is hands-on experience for your success?

1

2

3

4

5

6

1 Core Skills

2 Learning Curve

3 Tool Mastery

4 Project Experience

5 Industry Knowledge

6 Networking Value

Data Engineering

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You're starting a career in Data Engineering. How crucial is hands-on experience for your success?

1

2

3

4

5

6

1 Core Skills

2 Learning Curve

3 Tool Mastery

4 Project Experience

5 Industry Knowledge

6 Networking Value

Data Engineering

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