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ROLES and RESPONSIBILITIES - Design, build, and maintain end-to-end data pipelines from ingestion to curated, trusted data models. - Develop scalable and maintainable data transformation layers using modern transformation frameworks. - Design and optimize data warehouse schemas and data models to support reporting and analytics. - Write highly effective, production-grade SQL and optimize complex queries for performance. - Build, maintain, and monitor orchestration workflows, ensuring proper dependency management and data lineage. - Implement data quality, validation, monitoring, and reliability practices to ensure trusted datasets. - Make architecture and design decisions while balancing scalability, maintainability, and delivery speed. - Collaborate closely with analysts, engineers, and business stakeholders to understand requirements and translate them into robust data solutions. - Proactively identify improvements in data architecture, pipeline performance, and engineering practices. - Leverage Large Language Models (LLMs) and AI-assisted development tools to improve engineering productivity and accelerate delivery. - Build solutions that are production-ready, scalable, and resilient while maintaining high development velocity. Technical Skills - Expert-level proficiency in SQL, including complex query optimization, performance tuning, and advanced data modeling. - Strong expertise in data warehousing concepts, dimensional modeling, and analytical database design. - Hands-on experience with modern data transformation frameworks such as: - dbt - SQLMesh - Strong understanding of workflow orchestration, DAG design, dependency management, and data lineage. - Experience designing and maintaining reliable, production-grade data pipelines. - Strong knowledge of data quality frameworks, testing, validation, and monitoring. - Excellent systems thinking with the ability to design scalable and maintainable data architectures. - Proven ability to deliver high-quality solutions in fast-paced, agile environments. .
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.