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About This Role 8 to 15 years of experience Skills: Analytics Responsibilities: Design, develop, and deploy machine learning models using Python and Azure. Lead analytics projects in various domains like retail, finance, or consumer analytics. Build and train ML models, and deploy them using Python on Azure. Refactor outdated Python code to adhere to modern coding principles. Develop and deliver web applications using Python, Django, HTML, CSS, and RESTful APIs. Create APIs using Java, Python, and Node.js. Build customer health status analytics dashboards to enhance customer interactions. Implement automation projects using Python for web and API frameworks like Flask and FastAPI. Refine and maintain production code written in SQL, Python, and Spark. Collaborate with clients, implementation teams, and associates to ensure project success. Develop data ingestion tools using Python to extract data from relational databases and external APIs. Requirements: Bachelor's degree in Computer Science, Data Analytics, or a related field. Strong expertise in Python and at least one popular framework like Django, Flask, or Pyramid. Proficiency in SQL, SAS, or other statistical programming languages. Experience in developing unit tests and ensuring code quality. Knowledge of scripting languages such as Perl, Bash, or Shell scripting. Ability to write efficient and modular server-side code in Python. Strong technical skills in .NET Core, Python, Web API, and Azure/AWS. Familiarity with CI/CD automation using PowerShell, Linux shell scripts, and Python. Experience in building data ingestion and processing code using Python, PySpark, or similar languages. Track record of driving operational excellence through deep-dive analytics of business processes. Excellent coding skills and the ability to debug programs and integrate third-party services. Proven experience in developing analytics dashboards and visualizations for business insights. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.