The difference between Data Engineer, Data Scientist and Software Engineer

People are gradually feeling that data engineering is a subset of software engineering and many software engineers are working with data. The role of data in the software industry is increasingly important, the specialized branches working with data are gradually differentiated. So what is the difference between software engineer, data engineer and data scientist?

The LinkedIn report shows the skills that each role often has. Looking at the chart below, do you think you should call yourself software engineer, data scientist or data engineer?

1. What is Data Scientist? How to become Data Scientist?

Software Engineer

People who make applications and systems. Participate in every stage from design, writing code to testing and review. This role creates the product (and that product generates data).

The work of this role includes:

1. Frontend & backend development
2. Web application
3. Mobile application
4. Operating system development
5. Design software

Data Engineer

Developers of systems that aggregate, store and export data from a number of applications and systems created by software engineers. Data engineer possesses a niche of software engineer skills. 40% of the original data engineer is software engineer, this is one of the common career development directions.

The work of this role includes:

1. Advanced data structure
2. Distributed computing (distributed computing)
3. Concurrent programming
4. Knowledge of some new tools: Hadoop, Spark, Kafka, Hive, etc.
5. Create ETL / data pipelines

Data Scientist

As the creator of the analysis system on all data, it can be a one-time analytical model for the team to understand user behavior, or machine learning algorithm to implement software engineers' code and data engineers.

The work of this role includes:

1. Data modeling
2. Machine learning
3. Algorithm
4. Business Intelligence dashboards

The data team will change

Some trends show that the team structure working with data will have many changes. ETL process has become easier thanks to new tools (like Stitchdata.com) that allow software engineer to manage data pipelines. Large companies pull data engineers out of the software engineer team to create a focused work team with data. In some cases, data Scientists undertake both data synthesis and analysis.

The definition and requirements for all three roles will necessarily continue to improve, because ultimately data can only increase over time.

According to kipalog.com