#1. What does a data engineer do?

• Data engineers work in various settings to build systems that collect, manage, and convert raw data into usable information for data scientists and business analysis.

• These are some common tasks you might perform when working with data:

  • Acquire datasets that align with business needs.
  • Develop algorithms to transform data into useful, actionable information.
  • Build test and maintain database pipeline architecture.
  • Collaborate with management to understand company objectives.

#2. DATA ENGINEER vs DATA SCIENTIST

#3. Why pursue a career in Data Engineering?

• A career in this field can be rewarding and challenging.

• Providing easier access to data that data scientists, analysts, and decision-makers need to do their jobs.

• As long as there is data to process, data engineers will be in demand.

• LinkedIn listed it as one of its jobs on the rise in 2021.

• Data Engineering is also a well-paying career. The average salary in the US is $111,933.

• Many data engineers start as software engineers or business intelligence analysts.

#4. Skills Required to become a DATA ENGINEER

• Coding:

  • Proficiency in coding language is essential to this role. Common programming languages include SQL, NoSQL, Python, Java, R, and Scala.

• Relational and non-relational databases:

  • You should be familiar with both and how they work.

• ETL:

  • ETL is the process by which you'll move data from databases and other sources into a single repository, like a data warehouse.

• Data Storage:

  • Not all types of data should be stored the same way, especially when it comes to big data.

• Automation and Scripting:

  • It is a necessary part of working with big data simply because organizations are able to collect so much information.

• Machine Learning:

  • It can be helpful to have a grasp of the basic concepts to better understand the needs of data scientists on your team.

• Big Data Tools:

  • Data engineers don't just work with regular data. They're often tasked with managing big data. Some popular ones include Hadoop, MongoDB, and Kafka.

• Cloud Computing:

  • You'll need to understand cloud storage and cloud computing as companies increasingly trade physical servers for cloud services.

• Data Security:

  • Many data engineers are still tasked with securely managing and storing data to protect it from loss or theft.

#5. Get Certified

• A certification can validate your skills to potential employers, and preparing for a certification exam is an excellent way to develop your skills and knowledge.

• Options include the Associate Big Data Engineer, Cloudera Certified Professional Data Engineer, IBM Certified Data Engineer, or Google Cloud Certified Professional Data Engineer.

#6. Next Steps

• Whether you're just getting started or looking to pivot to a new career. Start building job-ready skills for roles in data with Google Data Analytics, IBM Data Science, or IBM Data Engineering Professional Certificates.