One of the defining technologies of the digital era is the cloud. From booking a cab to sharing pictures while traveling, most of our digital activities today are enabled by cloud computing. A key component of this is big data and analytics. The market that is projected to grow to $230 billion by 2025 presents a significant opportunity for organizations worldwide to make data-driven decisions, offer personalized experiences and improve their efficiencies too.
This has thrown open a wide array of opportunities for technologists. One of the most important among them is the cloud data engineer’s job, which plays a fundamental role in leveraging these opportunities. In this blog post, we discuss the roles, responsibilities, skills, and career growth of a cloud data engineer, along with what you can do to become one.
Interested in becoming a cloud engineer? Springboard can help! Explore everything you need to know about becoming a cloud engineer in this guide.
What Is a Cloud Engineer?
A cloud engineer combines software engineering and data science skills to design scalable big data infrastructures. They transform and prepare data for its intended purpose.
For example, if the data is needed for an automated recommendation engine, a cloud engineer will build data pipelines that collect and transform data from various sources such as the user’s account information, search terms, preferences on the platform, response to marketing messages, etc. Based on this, the recommendation engine will automate predictions in real-time for the user.
What Does a Cloud Engineer Do?
A cloud engineer builds and supports data infrastructures that enable data-driven decision-making. On the data layer, they collect, transform and publish data to be used for insights. At the infrastructure layer, they set up data processing systems that allow data scientists to build machine learning models and make accurate predictions.
Some of the key responsibilities of cloud engineers are:
- Designing, building, and operationalizing data processing systems
- Ensuring data and solution quality
- Integrate distributed systems into a single source of truth
- Design and maintain database systems
- Transform different forms of data into a usable format
- Operationalizing machine learning models
In any organization, a data engineer plays a foundational role in making data science, machine learning, and artificial intelligence possible. They are the architects and engineers behind the pipelines through which data flows and reaches its destination—be it data science teams or enterprise applications.
To make this happen, cloud engineers perform a range of tasks. Some of them are:
- Extracting data from various data source systems, transforming it into the staging area, and loading it into a data warehouse system (also known as ETL)
- Architecting, building, and launching data pipelines
- Using SQL, Cassandra, Bigtable, etc. to analyze and report on data characteristics
- Conducting systems monitoring across cloud infrastructures
- Automating processes for installation, configuration, monitoring, etc.
The following cloud engineer job description at Twitch in San Francisco offers a clear view of the responsibilities.
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Should You Add Cloud Certifications to Your Data Engineering Resume?
Data engineering is a rapidly growing field, and as such, is extremely competitive. Employers, especially cloud-native startups, are only looking for the most accomplished talent. To demonstrate your skills and set yourself apart, cloud certifications can be critical to data engineers looking to stand out from the competition.
Here are three reasons why you should get a cloud cerfification as a data engineer:
1. Employers prefer certified cloud data engineers—an AWS, Azure, or GCP certification is almost always an added advantage.
2. Certified cloud data engineers earn better—the Jefferson Frank Salary Survey reveals that 37% of respondents reported a salary rise post-certification
3. Certifications improve career growth—whether you prefer to be a specialist in a niche or a generalist leader of projects/teams.
What Is the Average Salary of a Cloud Engineer?
The average salary of a cloud-certified data engineer is around $131,000. According to Indeed, working in major tech hubs like San Francisco and New York will mean a higher salary.
The image below demonstrates the four cities in the US where cloud engineers can earn the highest salary.
How Do You Become a Certified Google Cloud Platform Engineer?
The Google Cloud Platform data engineering certification stands third among the top-paying certifications worldwide, also making it one of the most sought after. Primarily, this exam tests candidates on designing, building, and operationalizing data processing systems, operationalizing machine learning models, and ensuring solution quality.
How Do You Become a Certified Microsoft Azure Data Engineer?
The Microsoft Azure data engineer certification is ranked as the “most difficult to earn” mainly because of the exhaustive nature of the concepts you will be tested for. It also goes beyond the standard multiple-choice questions and includes various formats such as scenario-based questions that require you to reflect on the work you will do.
How Do You Become a Certified AWS Data Engineer?
The AWS data engineer certification is a specialist qualification—it is recommended that you have a minimum of five years of experience in analytics and also already hold an active practice or associate level certification. AWS itself offers several free courses and resources for you to prepare. However, as a practitioner’s exam, you are likely to be tested for your ability to apply these ideas to solve real-world problems.
Cloud Engineering Interview Questions
Depending on the job you are applying to, the industry it is in and the cloud platform they use, your interview might vary. Here are some of the most common questions asked in cloud data engineering interviews.
- Tell us about the hardest data engineering problem you solved. This question is meant to test your real-world experience in data engineering. Structure your answer by stating the problem clearly, outlining your solution, and explaining your approach to problem-solving.
- What ETL tools do you have experience with? Discuss the tools you have experience with and explain your proficiency level in each of them. If the job description requires you to know a specific tool, address your experience with those clearly.
- Tell us about the time when you have made improvements to data quality. An important part of a data engineer’s role is ensuring data quality and reliability. Discuss what efforts you’ve taken to achieve this. Also, tell the interviewers about any specific recommendations you made that improved the system overall.
- Do you focus on pipelines or databases? Explain your experience. If you focus on both, elaborate on how you do so.
- What common data engineering maxim do you disagree with? Many startups today require their employees to have an opinion and be able to passionately debate for it. This question is meant to test whether you can play an active role in debating your case. Speak confidently about what you disagree with, and make sure you explain why.
Whatever the questions may be, remember to be true to your experience and values. Interviewers don’t expect you to have all the answers at hand, they only need you to be skilled enough to find the answers you need. To demonstrate this, use examples from your past, focus on the problems you solved and explain your thought process. When you don’t know, accept that you don’t know and promise to learn.
Is Data Engineering the Right Career For You?
Data engineering occupies a unique space between software engineering and data science. You need to have both programming and data science skills to do your day-to-day job. You need not become an expert in either, but you need to have a strong understanding of both.
Moreover, you need to have multi-disciplinary skills in programming, networking, infrastructure architecture, data science, etc. You also need to have hands-on experience in several technologies such as big data tools, analytics products, cloud computing platforms, etc. You need to keep yourself updated about the latest advancements in these technologies and how it impacts your data infrastructure.
You need to be enthusiastic about solving problems and building sustainable systems. As one of the most rapidly evolving industries, data engineering will also require you to be adaptive and agile.
If the above sounds exciting to you, data engineering is certainly the right career for you. You don’t need an extensive data engineering background either. All you need is a computer science bachelor’s degree or some programming/analytics skills to kickstart your data engineering career.
Since you’re here…Are you interested in this career track? Investigate with our free guide to what a data professional actually does. When you’re ready to build a CV that will make hiring managers melt, join our Data Science Bootcamp which will help you land a job or your tuition back!