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Design and Build Data Solutions Design, develop, and maintain scalable batch and near real-time data pipelines using SQL and Python. Build, optimize, and support data ingestion, transformation, and orchestration processes in Snowflake and AWS. Develop reusable data assets, curated datasets, and data models that support analytics, reporting, operational workflows, and AI solutions. Create and maintain ETL/ELT frameworks to integrate data from multiple source systems. Ensure data solutions are scalable, reliable, secure, and cost-effective. Cloud Data Engineering Leverage AWS services such as S3, Lambda, Glue, ECS, and other cloud-native technologies to enable enterprise data processing and storage. Support cloud data warehouse and data lake architectures. Monitor, tune, and optimize data workloads to improve performance, reliability, and cost efficiency. Understand data quality, governance, lineage, and observability capabilities across data products and platforms. AI Enabled Engineering Productivity Leverage AI powered development tools and coding assistants to improve engineering productivity, accelerate software delivery, and enhance code quality. Utilize generative AI capabilities to support code generation, documentation creation, testing, troubleshooting, and data pipeline development. Identify opportunities to automate manual engineering processes through AI-enabled workflows and tooling. Evaluate and adopt emerging AI technologies and best practices while adhering to enterprise security, governance, and responsible AI standards. DevOps & Engineering Excellence Utilize GitLab for source control, CI/CD pipelines, automated testing, code reviews, and deployment automation. Implement DevOps best practices to improve delivery speed, quality, reliability, and operational support. Participate in production support, incident management, root cause analysis, and continuous improvement activities. Develop and maintain technical documentation, standards, and reusable engineering components. Agile Delivery & Collaboration Participate in Agile Scrum ceremonies including sprint planning, backlog refinement, daily standups, sprint reviews, and retrospectives. Collaborate with cross-functional teams to translate business requirements into scalable technical solutions. Contribute to architecture, data modeling, and design discussions.
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.