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Responsibilities: Design and operate production-grade ETL/ELT data pipelines for data ingestion, transformation and loading. Integrate data from APIs, databases, enterprise systems, SaaS, files, streams and cloud services. Develop batch, incremental, CDC and event-driven data pipelines. Design data models, schemas, data lakes and analytical datasets. Implement data quality, validation, monitoring, reconciliation and reliability controls. Build trusted datasets for analytics, reporting, operational visibility and AI/ML use cases. Design secure data integration across on-premise, AWS, Azure and hybrid environments. Ensure appropriate data security, access control, governance, lineage and auditability. Monitor production pipelines, troubleshoot incidents and improve performance, reliability and cost. Apply software engineering practices including Git, automated testing, CI/CD and Infrastructure as Code. Requirments: Minimum 3–5 years of experience in data engineering, cloud data engineering, analytics engineering, software engineering, or a related discipline At least 2 years of hands-on experience designing, building, and operating production-grade data pipelines Demonstrated experience with data extraction, ingestion, ETL/ELT, transformation, data modelling, and data quality Experience using AWS and/or Azure native data capabilities Experience integrating data from APIs, databases, enterprise systems, files, or streaming sources Experience implementing batch, incremental, CDC, and/or event-driven data pipelines Experience working with on-premises and/or cloud environments, with an understanding of hybrid integration patterns Experience applying software-engineering practices such as version control, automated testing, CI/CD, monitoring, and Infrastructure as Code to data solutions
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.
