Data Engineer, Machine Learning Engineer, and Site Reliability Engineer What are the differences?
What are the differences between ‘Data Engineer’, ‘Machine Learning Engineer, and ‘Site Reliability Engineer’? Let’s find out! These three jobs are just examples of emerging jobs due to the creations of new technologies, whether AI or machine learning, that have become a necessary part of our lives.
The demands of these emerging jobs are increasing, along with the earnings. However, one issue is that these job titles somehow sound the same, confusing for those who are outside the field.
Today, we’re going to address three jobs that come with the title of ‘Engineer’ but their details are more diverse than you’d expect; ‘Data Engineer’, ‘Machine Learning Engineer, and ‘Site Reliability Engineer’.
The word ‘Engineer’ means a person who builds something, but what each one builds is the core of each job. Let’s see what these three counterparts build.
What is Data Engineer (DE)?
Is it the builder of data? No, it isn’t. Data Engineer (DE) is a person who is responsible for designing and maintaining data infrastructure. Data engineers also perform the ETL (Extract-Transform-Load) process to create a data pipeline to organise raw data.
Data is the heart of businesses, and businesses are in desperate need of having the one who can design the system that allows them to store, transfer, and effectively utilise data. DE is that person who provides the data infrastructure to facilitate others’ works.
At Sertis, our DE is responsible for analysing and creating the data systems that meet clients’ requirements, so they can perform data analysis to improve their business decision. DE will create systems that facilitate data extraction from sources, and select tools and frameworks that suit clients’ needs. Lastly, DE will build a data pipeline and data warehouse to organise all data in the company.
Basic skills and knowledge that DE needs are knowledge of programming languages, data management tools and software, data warehouse and database. At Sertis, we use SQL Database for the tool, and Python Scala and Java for the programming languages. We also use the software as Hadoop & Hive, Apache Spark, and Airflow.
However, we have diverse clients with different requirements, so our DE will get a chance to experience several kinds of challenges, which is extremely fun, we must say.
Learn more about our data engineer at:
What is Machine Learning Engineer?
This position is a mixture of data works and software development. A machine learning engineer or MLE is a person who develops a machine learning model and trains it to automatically process and analyse data, a huge amount of data that is beyond human capability.
MLE has two main responsibilities. One is to develop the model that other teams, for example, data science and AI researcher, created to the production level that can handle numerous data. The other is to build an algorithm and train model, using data that a data engineer transformed into a suitable format, in order to build a self-running model.
At Sertis, our MLE will perform model training, model optimisation, and model prediction, and also facilitate model deployment on Cloud or other IoT devices and make sure that it supports heavy user traffics.
Basic skills and knowledge that MLE needs are computer science background, algorithm theories, programming languages, and machine learning and deep learning framework. At Sertis we use Python, C++, and GO, and frameworks such as TensorFlow, Pytorch, MXNet, CAFFE, and ONNX.
MLE at Sertis will get a chance to work for clients from leading companies who wish to tackle their operation issues using machine learning models. As MLE, you’ll help solve different kinds of problems and make people’ lives easier.
Learn more about our machine learning engineer at:
What is Site Reliability Engineer?
The last job title that we’d like to cover today is a little bit more different because it is all about software. Here we introduce you to a Site Reliability Engineer or SRE. Nowadays, there are more and more complex software features that come with more issues to handle.
That is why SRE was generated. SRE is a person who develops software focusing on ‘reliability’ and long-term use. Site reliability has become one of the tasks in DevOps, the union of team members working together throughout the cycle, focusing on delivering applications and services as fast as possible. SRE is the combination of software developers and IT operations.
SRE’s main responsibility is to work along with software developers. After the code is written, SRE will step in to improve the software’s reliability, flexibility and unexpected incidents response, as well as automate the operational tasks for real-time incident response systems, and make it extensible for future features.
Site Reliability Engineering first originated at Google. Google has published a book called Site Reliability Engineering presenting a method of tackling software issues by weighing more on reliability.
Skills SRE needed are mainly on programming languages (At Sertis, we use Python and Java), software development based on reliability, flexibility, and incident response, knowledge of CI/CD, and knowledge of secure and effective software deployment on infrastructures as Cloud.
Let’s compare these three positions with this scenario:
One client wanted to do a project on developing a machine learning model for data analysis and develop software from the model.
- Data Engineer would extract all required data, organise it, and build a data pipeline and load the data into a data warehouse.
- Machine Learning Engineer would feed and train the analytical model with data to make it self-running and scale it out to the production level.
- Site Reliability Engineer would develop software focusing on reliability and automatic incident response.
Are you starting to get the picture of how these three positions are different and how they cooperate?
At Sertis, we believe that to develop new technology, whether it is data, AI, or machine learning, cooperation and knowledge sharing from experts in every field is the key to success, because we all have diverse expertise and all kinds of expertise matter.
Knowledge sharing and flexibility as in Scrum and Agile practice that allow every member to shine their best and contribute to the success is the core of the working culture at Sertis.
If you feel like we suit you, find more information on opening positions at: www.careers.sertiscorp.com/open-positions
Written by: Sertis