Best Entry-Level Programming Jobs

Best Entry-Level Programming Jobs. Before making the decision to pursue a career in programming, you might want to understand more about the coding job market. Look nowhere else! You may traverse the large and dynamic world of programming careers with the aid of our list of the top nine entry-level programming positions. There are many chances in coding for those with the correct talents and mindset, whether they want to change careers or upskill.

We’ll examine the various types of entry-level programming jobs and what they entail, from web development to data analysis, software engineering to machine learning.

What does an entry-level programming job entail?

In many businesses, entry-level programming positions entail collaborating with more seasoned programmers, typically senior engineers. Tasks are given to the junior by the senior. The workload varies according to each organization. A good senior will make sure to assign tasks that are both challenging and within the capabilities of the beginning programmer.

The junior should be expected to learn or be able to use a programming language for the tasks. You will learn the existing code base used by the business as a beginning software engineer.

For instance, implementing backend logic and utilizing Application Programming Interfaces would be coding tasks for an entry-level web developer position where you create code in JavaScript (APIs). APIs make it simpler for your browser to communicate with the database. Also, you must adhere to recommended practices, such as developing tests for your code. Learn how to use collaborative platforms like Trello and Jira as well.

You could need to learn new frameworks, databases, tools, or even programming languages, depending on the organization you work for. When learning on the job, speed is crucial.

Entry-level programmers’ work has to be overseen by more seasoned programmers. You must ask for clarifications and accept criticism well.

A junior could occasionally feel as though they are only given the “minor chores,” even though they would really like to do more. Continue working on improving yourself as a craftsperson as long as you are still learning.

Have an open mind, ask questions, and develop your independent problem-solving skills (Google, Stack Overflow, and now ChatGPT should be your good friends).

9 Best Entry-Level Programming Jobs

You’re in luck if you want to pursue a profession in science, technology, engineering, or mathematics (STEM). According to the United States Bureau of Labor Statistics, a career in computing is a sure bet for the next five years and a job for the future, despite all the changes brought on by AI.

What types of programming jobs can you get as a beginning, then, is the ongoing question. Let’s investigate:

1. Entry-level web developer

The main responsibility of an entry-level web developer is to create web-based apps. These are applications that must be accessed through a browser like Google Chrome. Web apps are more adaptable than websites. You could, for instance, make payments.

The specific web development function depends on the business. You might work on already-existing applications or create brand-new ones. Several stages of the Software Development Life Cycle (SDLC), such as gathering project requirements, testing, and maintenance, may also involve you.

Your choice of programming languages is also greatly influenced by the organization. A few of the most well-known ones are HTML, CSS, JavaScript, Python, and Ruby. Databases, APIs, fundamental SEO, content management systems (CMS), and web development frameworks are additional topics you should learn about.

You can work as a full-stack, frontend, or backend engineer as a beginning web developer.

2. Junior DevOps engineer

Another great position to aim for in entry-level programming is this one. But, you must understand what DevOps is in order to comprehend the work of a junior DevOps engineer. DevOps is a blend of “development” and “operations,” on the surface. Collaboration is the key component of DevOps, though. DevOps includes concepts like “Scrum” and “Agile,” which you may have heard of. DevOps eliminates boundaries between the many teams and departments who are in charge of successfully delivering software. In order to automate processes and set up testing tools, as well as various configurations and integrations, a junior DevOps engineer uses a set of DevOps principles, such as continuous integration and deployment (CI/CD).

You can also be in charge of performing performance system monitoring as a young DevOps engineer. Examine the logs to find instances of system failure. Depending on the objectives of the project, you might also employ mathematical models to forecast the results of specific software development strategies.

By doing this, you aid in the smoother deployment of software by your development team. Even in production, new changes can be immediately merged, requiring substantially less work from the software team and other required parties. Understanding the full SDLC, the infrastructure on which it runs, and ideas like Infrastructure as a Service are just a few of the abilities required for a junior DevOps post (IaaS).

Also, you’ll require familiarity with the containerization and AWS, Google Cloud, or Azure cloud computing platforms (Kubernetes, and Docker)

As a junior DevOps, you’ll use a variety of programming languages, including Python, Ruby, Java, Golang (Go), and JavaScript.

3. Entry-level cloud engineer

Cloud computing is a cloud engineer’s main area of interest. They assist a business or organization in “migrating to the cloud,” in other words. This could imply that an organization’s servers were housed on-site at the business, as in “on-premises” or “on-prem,” for example.

• Helping businesses host their applications, databases, and other digital assets on the cloud will be a part of your duties as a cloud engineer. You’ll assist with maintenance as well.
• They may occasionally switch cloud providers as well, and you should be able to help them make the transition more quickly.
• You will collaborate with more seasoned developers as a junior cloud engineer to:
• Enhance current cloud infrastructure
• Choose superior cloud solutions for your business.
• Create and release cloud-based software
• Deployment and infrastructure issues must be resolved.
• Make sure the appropriate people may access and maintain the security of cloud-based systems.
• Make careful to adhere to recommended practices for cloud computing while installing applications there.
• Building systems that other businesses use for cloud computing will be part of your cloud engineer role if you wind up working for a company that creates cloud infrastructure, like Amazon.

Understanding the fundamentals of cloud computing, being familiar with Linux, and being proficient in programming in languages like Java, Python, Ruby, and Golang are requirements for being a successful cloud engineer (Go). Also, you’ll be able to construct certain cloud applications and services, comprehend databases, use APIs, and have a basic understanding of DevOps.

A plus is also having knowledge of DevOps technologies and cloud infrastructure tools like OpenStack, AWS, Google Cloud, and Azure. Obtaining some cloud certifications is a great approach to show that you are knowledgeable about these technologies and concepts since you may not have much experience with them. While larger firms maintain them separate, smaller businesses frequently mix many cloud computing roles into one, such as a cloud engineer function.

4. Entry-level mobile app developer

A junior mobile app developer spends the most of their time developing mobile apps for the iOS or Android platforms. Before we get started, it’s crucial to understand the distinctions between mobile apps and online apps.

You could sometimes create cross-platform programs (which work on both iOS and Android and you only need to write the source code once.) You may also be involved in other aspects of the SDLC process as an entry-level programmer, such as obtaining project requirements and creating new product features. You must adhere to best practices to guarantee that the application’s performance, quality, and responsiveness are satisfactory. Debugging and writing tests are also part of your day.

Objective-C, Kotlin, C#, Swift, and Java are some popular mobile development programming languages. You must be comfortable dealing with databases, APIs, and mobile application frameworks.

5. Junior data analyst

In this capacity, you will collect and handle massive amounts of data (referred to as “big data”) and then evaluate them using statistics. You will then gain useful insights and communicate them to the appropriate parties. To communicate your findings as a data story, you’ll use several data visualization tools such as flowcharts, charts, graphs, Sankey diagrams, and dashboards.

A degree in statistics, engineering, or mathematics may offer you an advantage, but it is not required. Obtaining certifications such as Microsoft’s Power BI Data Analyst exam (PL-300) will provide you an advantage while pursuing a career in data analysis.

More on this in our comprehensive guide to becoming a junior data analyst, but the expertise required to prosper as a data analyst includes the following:

• Data tools like Excel
• Programming language knowledge (R, SAS, Python)
• Data visualization
• Data visualization tools like Power BI and Tableau
• SQL and SQL database know-how
• Other database querying languages
• Data mining, blending, cleaning, discovery, manipulation, and data wrangling or munging
• Basic web development skills are a plus (HTML, CSS, and Javascript)
• Statistical tools might also come in handy, for example, SPSS

It is critical to differentiate between data analysts, data scientists, and data engineers. Data scientists utilize machine learning to derive predictions from data, and data engineers design the tools that analyze and interpret the data.

Data analysis is perhaps the least technical of the three, and it is currently one of the most common entry-level programming positions. Data analysis is a great entry-level role from which to move to more technical positions like machine learning engineer or data engineer.

6. Entry-level data scientist

A junior data scientist collaborates with a senior data scientist on advanced analyses. In advanced analytics, statistical modeling and machine learning are utilized to generate data-driven recommendations. You will then share your findings with other stakeholders.

You can also create data science models and features that improve an existing product, such as models that offer user suggestions (similar to Amazon’s “often bought together” feature). The function also includes data analyst activities such as data munging, data visualization, and documenting your approach from start to finish.

As a data scientist, you will require the following skills:

• Statistics knowledge
• Machine Learning algorithms
• An understanding of relational databases (SQL-based databases like Microsoft SQL Server or MySQL) and data warehouse systems like Hive
• A good grasp of programming languages like R and Python
• Working knowledge of the Unix or Linux command line
• Comprehend Extract, Transform, Load (ETL) and Extract, Load, Transform (also ELT) data transformation procedures
• Data and Business Intelligence tools like Tableau and Looker
• Data Science collaboration tools like DagsHub

Data scientists and data analysts frequently collaborate to prepare and analyse data for use in models.

A degree in math, physics, or engineering is advantageous because the data scientist profession is highly academic. Because many businesses are still unfamiliar with handling massive datasets, data scientists are in high demand. Yet, transitioning into data engineering may be a wise decision in the long run.

7. Junior data engineer

As a junior data engineer, you will be responsible for data extraction, wrangling, preparation, and purification, just like a data analyst. But, in this entry-level programming position, you go the extra mile by automating these operations. You are also the one who creates the systems that data scientists rely on. If you want to learn more about the distinctions between a data scientist and a data engineer, see our guide.

You will also be accountable for the following:

• Creating, managing, and maintaining data pipelines
• Recommending how to fix issues with data quality
• Creating and managing data platforms

You’ll also work with data scientists to help them create business analytics features or features that can help solve machine learning problems.

The skills that you need to thrive as a junior data engineer include:

• A solid understanding of core computer science concepts
• Databases (managing tables, doing joins and data aggregation, as well as inserting, updating, and deleting records efficiently)
• SQL
• Programming languages (Python, Scala).
• Some experience building and designing large-scale applications, end to end
• Containerization (Kubernetes, Docker)
• Some knowledge of building data pipeline systems
• Some experience working with data workloads
• Data modeling exposure
• ETL knowledge (OLAP and OLTP)
• Data integration (create a data pipeline from several data platforms like Hadoop, Spark, and Kafka).

A data engineer is also referred to as a data platform engineer, data infrastructure engineer, data support engineer, ETL manager, or database manager.

The data engineer role is closer to “real-world” problems than the data scientist role.

8. Entry-level machine learning engineer

Machine Learning is another rapidly expanding field, as the notion finds more and more applications. Our entire machine learning engineer guide contains more information about what activities are anticipated, however as a junior, your day-to-day responsibilities may include:

• Assembling datasets
• Building ML models based on the datasets
• Ensuring that your model scales and is performant
• Ensuring that there is good information flow between various components in the system

The skillset that you need to become a great MLE (at least over time) is:

• A good command of SQL
• Programming language knowledge (Javascript, R, Python, Scala, Javascript, Java, and C++)
• Some experience building highly-scaled distributed systems, for example, recommendation systems, and distributed computing frameworks (Apache Mahout)
• Familiarity with machine learning fundamentals (algorithms and data structures, ML tools like TensorFlow and PyTorch)
• Experience working with big datasets
• Data visualization know-how will also come in handy
• Conversance with metrics
• Debugging models and their misclassifications
• Being aware of your own and other people’s biases and accounting for them in your models
• Probability and statistical knowledge
• Data wrangling and analysis
• A grasp of Unix tools

Don’t be disheartened if you don’t have a STEM degree. You can begin with “more abstract ML,” where you may not understand the underlying mechanisms but can execute ML solutions. Using pre-trained Amazon models, as well as high-level frameworks and tools, is one example. You will eventually be able to learn about the “behind-the-scenes” of ML.

Working in product-focused or personalization-related tasks as an entry-level MLE will go a long way toward helping you become a rock star MLE. Depending on where you live, getting an entry-level MLE may be difficult. You may start as a data analyst, then move on to machine learning and an MLE role.

After all, some say that an MLE is nothing more than a data scientist with great programming skills.

9. Entry-level software engineer

Thus far, we’ve just looked at entry-level software engineering positions. You are a software engineer whether you are an entry-level web developer creating web applications, a mobile developer creating Android, iOS, or cross-platform apps, or even a data engineer.

The exciting aspect is that the software engineering growth curve can go in any direction. You could continue your career as a software engineer. Your development route could look like this:

• Mid-level software engineer
• Senior engineer
• Staff engineer
• Principal engineer
• Engineering fellow
• Distinguished engineer

This is known as the “individual contributor path,” because it does not allow you to manage individuals. You can also go the “people” path and work as a product manager, engineering manager, tech lead, CTO (chief technology officer), or CIO (chief information officer).

Another option is to specialize in cloud engineering, DevOps, machine learning, or data and work your way up the ranks. It’s also worth noting that some firms require a few years of software engineering expertise for careers in DevOps and cloud engineering.

This is due to the high level of responsibility associated with these roles. You may be in charge of the entire architecture on which the company’s product is built. If you have no past experience, a lot of things can go wrong.

Conclusion

FAQs on Best Entry-Level Programming Jobs

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