Data is something that matters more than anything in the current time. We have seen a rapid increase in data over the past few years. Since the amount of data is increasing, businesses are in dire need of experts who can handle extensive data related to the customer details, service or product performance, and competitor research. Also, there is a need for professional and expert developers. They can manage the complexity, which is increasing on the apps and websites. These two needs are giving rise to two promising technical fields: data engineer and software engineer. It’s not very clear to differentiate between these fields since they overlap sometimes; however, they have different roles and areas of working.
Data Engineer in brief
A data engineer is a person who is responsible for making the data accessible to the people within the same organization. The data engineer aims to ensure that the data’s end-user – an analyst, executive, or a data scientist, gets the accurate data using which insightful decisions can be made by the business. In recent times, data engineers use several tools like Kafka, Spark, any cloud provider like AWS; at the same time, a few newer data warehouses/databases include Snowflake and MongoDB. The businesses choose to update their stacks and leverage the technologies as it allows the data related teams to move faster than before – with a much faster pace and delivering the results to the stakeholders. A company looking for data engineers needs to focus on their data warehouses and utilize the in-depth knowledge of making the information into query while continually working to process or ingest data. The data engineers also focus on the data flow more and know how they collaborate. Any individual wishing to become a data engineer should look for a Data Engineering Certification.
Data engineers work includes:
- Distributed computing
- Advanced data structures
- Knowledge of emerging and new tools like Spark, Hadoop, Hive, Kafka, etc.
- Concurrent programming
- Building ETL or data pipelines
Software Engineer in Brief
As similar to a data engineer, the software engineer also works on building out the data pipelines. The software engineer can also be called as an infrastructure or platform engineer. The software engineers need to be good with data modeling, SQL, and similar technologies like Hadoop, AWS, Spark. They must work on things at the macro level. It is their responsibility to build out the cluster scheduler and manager, the distributed cluster system, and implementing code to make the things work and function efficiently and faster. They are also good at programming, unlike data engineers. Usually, they will work in Java, Python, Scala, Golang, and a few DevOps tools like Kubernetes, Docker, or some CI/CD tool (Jenkins). All of the skills mentioned above are critical for software engineers. It is because they continuously test and deploy new services and make the systems more efficient. If the machine learning or data science team does not have a strong software engineer to build their platform, their models won’t be maximized fully. Hence it is essential to understand, notably, when incorporating Machine learning and Data science teams. The software engineers also need to scale out the systems since the platform grows to handle more and more data and find ways to improve. Software engineers collaborate with machine learning and data science teams to understand and know the prerequisites of the conditions needed to support any machine learning model.
Software engineers work includes:
- Operating system development
- Mobile Apps
- Web Apps
- Frontend and Backend development
- Software Design
Data engineer v/s Software engineer
If a company is looking for someone who should focus extensively on pulling the data from varied data sources or API, before transforming the data and then moving it somewhere else, the company is looking for a data engineer. A data engineer who is good at working with data warehouses and using the tools like Looker or Tableau for visualization is counted as a quality data engineer. They are usually the ones who have done the data engineering certification.
If a company is looking for someone who should wear multiple hats and build highly distributed and scalable systems, it is looking for a software engineer. Hiring managers usually need someone who can multi-task since they have budget constraints, and hence this type of job role is mostly seen in smaller teams and companies. The software engineers are also good coders and have experience using the DevOps tools. Although software engineers do more than data engineers, they are not as strong in data engineering’s practical details. Mainly working within a data warehouse and querying the data.
It also gets challenging for companies to know which job type to recruit for. It is not rare to see that the companies post the advertisements that they need a software engineer looking for a data engineer. If you want to bring the right candidate to the door, it is necessary and essential for the companies to understand which responsibilities and work type are you aiming to get fulfilled.
Bottom Line
Data engineers can’t work with DevOps tools like Kubernetes or Docker, and the Software engineers can work on data visualization tools like Looker or Tableau. Engineers need to become proficient and expert with several tools and constantly hone their skills to survive in the ever-increasing competition. If they want to fight against the tight competition created in the present world, they better learn how to develop a new skill.
Both data engineer and software engineer roles keep on evolving. In the current time, none of it is a dominating technical field as they both hold equal importance in any company. Also, at the time, data engineers and software engineers work in collaboration to give better results. To excel in your career as a Data Engineer, you should look for a Data Engineering Certification.
Laila Azzahra is a professional writer and blogger that loves to write about technology, business, entertainment, science, and health.