Back

Data Science Developer with Azure (Microsoft Azure) Salary in 2024

Share this article
Total:
76
Median Salary Expectations:
$5,285
Proposals:
0.6

How statistics are calculated

We count how many offers each candidate received and for what salary. For example, if a Data Science with Azure (Microsoft Azure) with a salary of $4,500 received 10 offers, then we would count him 10 times. If there were no offers, then he would not get into the statistics either.

The graph column is the total number of offers. This is not the number of vacancies, but an indicator of the level of demand. The more offers there are, the more companies try to hire such a specialist. 5k+ includes candidates with salaries >= $5,000 and < $5,500.

Median Salary Expectation – the weighted average of the market offer in the selected specialization, that is, the most frequent job offers for the selected specialization received by candidates. We do not count accepted or rejected offers.

Where is Microsoft Azure used?

 

Cloudy with a Chance of Streamlining



  • Picture a world where code deployments fly up to the sky. Azure's DevOps services make this a breeze, chucking updates into the wild blue yonder with more automation than a robot butler.




Binge-Watching for Machines



  • Azure's IoT services turn ordinary toasters into binge-watching data hogs, relentlessly streaming bytes like they're the latest hit TV series.




Save the Planet, One Virtual Server at a Time



  • Deploy a legion of virtual servers without cutting down a single tree. Azure’s eco-friendly cloud keeps physical hardware to a minimum, giving a whole new meaning to virtual "green" space.




Fortune Telling with Data



  • With Azure's AI and Machine Learning, you can predict the future like a techno-wizard, forecasting sales like reading tea leaves but with more graphs and less mess.

 

Microsoft Azure Alternatives

 

Amazon Web Services (AWS)

 

Cloud computing platform offering computing power, database storage, content delivery, and other functionality.

 


// Example of launching an EC2 instance with AWS SDK for JavaScript
const AWS = require('aws-sdk');
AWS.config.update({region: 'us-west-2'});
const ec2 = new AWS.EC2({apiVersion: '2016-11-15'});
const params = {
ImageId: 'ami-0abcdef1234567890',
InstanceType: 't2.micro',
MinCount: 1,
MaxCount: 1
};
ec2.runInstances(params, function(err, data) {
if (err) console.log("Could not create instance", err);
else console.log("Created instance", data.Instances[0].InstanceId);
});



  • Most extensive global cloud infrastructure

 

  • Comprehensive set of services and tools

 

  • Per-minute billing for better cost management

 

  • Can be overwhelming for new users

 

  • Occasional service disruptions

 

  • Pricing complexity may lead to unexpected costs




Google Cloud Platform (GCP)

 

Offers services in all major spheres including compute, networking, storage, machine learning, and IoT.

 


// Example of creating a Compute Engine instance with Google Cloud SDK for Python
from google.cloud import compute_v1
project = 'your-project-id'
zone = 'us-central1-a'
machine_type = 'zones/{}/machineTypes/n1-standard-1'.format(zone)
compute = compute_v1.InstancesClient()

instance = compute_v1.Instance()
instance.name = 'instance-1'
instance.machine_type = machine_type

# Define the disk
disk = compute_v1.AttachedDisk()
disk.initialize_params.source_image = 'projects/debian-cloud/global/images/family/debian-9'
disk.auto_delete = True
disk.boot = True
instance.disks = [disk]

# Create the instance
response = compute.insert(project=project, zone=zone, instance_resource=instance)
print(response.result())



  • Seamless integration with Google's suite (Analytics, Ads, etc.)

 

  • Data and analytics are robust

 

  • Friendly to Kubernetes and open-source projects

 

  • Smaller network compared to AWS

 

  • Billing is complex

 

  • Limited enterprise support compared to AWS and Azure




IBM Cloud

 

Hybrid cloud platform offering a suite of AI, data, analytics, and IoT services.

 


// Code for authenticating and starting a service with IBM Cloud SDK for Node.js
const { IamAuthenticator } = require('ibm-cloud-sdk-core');
const CloudantV1 = require('@ibm-cloud/cloudant');

const authenticator = new IamAuthenticator({
apikey: 'your-apikey',
});

const cloudant = CloudantV1.newInstance({
authenticator: authenticator
});

cloudant.setServiceUrl('https://your-cloudant-url');

const createDb = async () => {
try {
await cloudant.putDatabase({ db: 'my-database' });
console.log('Database created');
} catch (error) {
console.error('Error creating database', error);
}
};

createDb();



  • Strong focus on AI and machine learning with Watson

 

  • Secure and reliable

 

  • Great choice for hybrid cloud deployments

 

  • Complex pricing tiers

 

  • User experience is less intuitive

 

  • Smaller market share and community

 

Quick Facts about Microsoft Azure

 

Azure's Celestial Birth

 

Once upon a time in the cosmic realm of 2008, the tech wizards at Microsoft conjured up a mystical cloud creature named 'Project Red Dog.' A year later, it metamorphosed into what mortals now revere as Microsoft Azure, a colossal digital canvas for creative coders and IT magicians to sculpt their cloud-based dreams.



Evolution of the Azure Species

 

Azure is like the Darwin’s finches of cloud computing—constantly evolving. It started with a simple set of services, and now it's an ever-growing ecosystem with over 200 products and services. From virtual machines that shape-shift to your needs, to AI services that foresee the future like an oracle, Azure's versatility is its superpower!



Groundbreaking Azure Incantations

 

The magicians at Azure didn't stop with pulling rabbits out of hats. They conjured up the Azure DevOps platform, transmuting mere muggles into agile wizards, able to cast CI/CD (Continuous Integration/Continuous Deployment) spells with ease.

 


// A snippet of an Azure DevOps spell for Pipeline conjuring
trigger:
- master

pool:
vmImage: 'ubuntu-latest'

steps:
- script: echo "The alchemy of CI/CD begins!"
displayName: 'Invoke Spell'

What is the difference between Junior, Middle, Senior and Expert Microsoft Azure developer?







































Seniority NameYears of ExperienceAverage Salary (USD/year)Responsibilities & ActivitiesQuality
Junior Azure Developer0-250,000-70,000

  • Execute simple cloud maintenance tasks

  • Develop basic functions within Azure under supervision

  • Learn and assist with cloud infrastructure setup


Learning and developing competency
Middle Azure Developer2-570,000-100,000

  • Design and implement moderately complex Azure solutions

  • Contribute to cloud architecture decisions

  • Automate deployments and scaling processes


Competent, able to work independently on most tasks
Senior Azure Developer5-10100,000-140,000

  • Lead complex Azure project implementations

  • Optimize cloud resources for performance and cost

  • Mentor junior and middle developers


High-quality work; role model for lower levels
Expert/Team Lead Azure Developer10+140,000-180,000

  • Define strategic direction for Azure development within the organization

  • Lead cross-functional projects with complex integrations

  • Drive innovation and adoption of best practices


Exceptional quality; leads and improves team performance

 

Top 10 Microsoft Azure Related Tech




  1. Azure SDKs & Command-Line Tools


    Imagine arming a wizard with a calculator; that's what Azure SDKs and CLIs do for developers! These tools let devs cast spells in their preferred programming language, conjuring up resources within Azure faster than a caffeine-fueled coder at a hackathon. Whether you're a Python charmer, JavaScript juggler, or a .NET necromancer, these SDKs are your wands for cloud wizardry!



    # Deploy an Azure VM using Azure CLI
    az vm create \
    --resource-group MyResourceGroup \
    --name MyVm \
    --image UbuntuLTS \
    --generate-ssh-keys

 


  1. Azure DevOps & GitHub


    Azure DevOps and GitHub are like peanut butter and jelly for your continuous integration sandwich. With pipelines more bendy than a contortionist, these services will automate your build-test-deploy cycle smoother than a Tesla on autopilot. Merge requests and version control will seem as easy as stealing candy from a baby - though please don't do that.



    trigger:
    - main

    pool:
    vmImage: ubuntu-latest

    steps:
    - script: echo "Hello, world!"

 


  1. Azure Functions


    Azure Functions are like little minions of the cloud, diligently running background tasks or reacting to events. These serverless sidekicks can scale like Ant-Man and save you the hassle of server management, leaving you free to binge-watch your favorite series while they handle the grunt work. Just be sure not to feed them after midnight!



    module.exports = async function (context, req) {
    context.log('JavaScript HTTP trigger function processed a request.');
    // Function logic goes here.
    };

 


  1. Azure Cosmos DB


    Think of Azure Cosmos DB as the Swiss Army knife of databases: multi-model, globally distributed, and more scalable than a rock climber hopped up on energy drinks. With turnkey global distribution, you can cater to your users around the world as if you had Santa's sleigh - and no, reindeer are not included!



    // Query using Azure Cosmos DB SQL API
    SELECT * FROM c WHERE c.username = "codingninja"

 


  1. Azure Kubernetes Service (AKS)


    Azure Kubernetes Service rolls up like a gangsta in the cloud container orchestration neighborhood. AKS makes managing your containerized applications look like a walk in the park - though, in reality, you may feel like a ringmaster juggling with Docker images. Fear not, for AKS will keep your containers in line like well-behaved poodles!



    # Create an AKS cluster
    az aks create \
    --resource-group myResourceGroup \
    --name myAKSCluster \
    --node-count 3 \
    --enable-addons monitoring \
    --generate-ssh-keys

 


  1. Visual Studio & VS Code


    Visual Studio and VS Code are like Batman and Robin for Azure development. These superhero IDEs come packed with IntelliSense, debugging powers, and direct integration with Azure - allowing you to save the day (code) with elegance and efficiency. Watch out Joker (bugs), the dynamic dev duo is here to thwart your nefarious schemes!

 


  1. Azure Logic Apps


    Logic Apps are basically if-this-then-that for grownups: a visual designer for automating workflows without writing a single line of code. They hook up with hundreds of services faster than teenagers at a prom. Just don't let their convenience make you lazy, or you might find yourself using a Logic App to fetch your coffee!

 


  1. Azure SQL Database


    Azure SQL Database is like a butler for your database management, serving up high availability, automated backups, and performance tuning on a silver platter. It allows you to focus on writing queries like Shakespeare rather than fiddling with database knobs and dials - unless that's your jam, of course!

 


  1. Azure Machine Learning


    If Tony Stark's J.A.R.V.I.S. did machine learning, it would be using Azure ML. This suite trains models faster than a barista on his first day, and with less confusion. Whether your data is pictures of cats or the secrets of the universe, Azure ML helps you mine wisdom from the chaos - while you take all the credit!

 


  1. Azure Active Directory (AAD)


    Azure Active Directory is the bouncer at the club of your application, deciding who gets the VIP treatment and who's left out in the cold. AAD's single sign-on and multi-factor authentication ensure that only invited guests party in your app, keeping the party crashers (aka hackers) at bay.

 

Subscribe to Upstaff Insider
Join us in the journey towards business success through innovation, expertise and teamwork