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About Smart Working At Smart Working, we believe your job should not only look right on paper but also feel right every day. This isnt just another remote opportunity - its about finding where you truly belong, no matter where you are. From day one, youre welcomed into a genuine community that values your growth and well-being. Our mission is simple: to break down geographic barriers and connect skilled professionals with outstanding global teams and products for full-time, long-term roles. We help you discover meaningful work with teams that invest in your success, where youre empowered to grow personally and professionally. Join one of the highest-rated workplaces on Glassdoor and experience what it means to thrive in a truly remote-first world. About the Role We are looking for a hands-on Software / Data Engineer to own and maintain a modern cloud-based data platform focused on EV repair cost intelligence and analytics. You will work across backend engineering, AWS infrastructure, data pipelines, and analytics systems, helping maintain and evolve a platform used by insurers and automotive organisations to better understand EV repair risk and pricing. This is a highly practical engineering role suited to someone who enjoys taking ownership of systems end-to-end, solving real operational problems, and improving reliability, scalability, and maintainability across a growing platform. The environment is lean, collaborative, and fast-moving, with significant autonomy and responsibility from day one. \n Responsibilities Own and maintain cloud-based data pipelines and backend systems across the AWS stack. Run and support monthly ingestion and processing workflows using AWS services such as S3, Lambda, Glue, Athena, and Step Functions. Maintain and improve the Python codebase, dependencies, and backend services. Support and enhance the client-facing analytics dashboard and API delivery layer. Perform data quality validation, troubleshooting, and issue resolution across the platform. Improve API performance, scalability, and reliability. Help redesign and modernise data structures and vehicle make/model mapping systems. Support the productionisation of a cloud-based repair database. Reduce technical debt and improve engineering standards across the stack. Integrate and manage third-party data providers and ingestion workflows. Work independently to identify platform improvements and deliver pragmatic solutions. Use AI tools and automation to improve engineering productivity and operational efficiency. Requirements 25+ years of experience in software engineering, data engineering, or backend engineering roles. Strong Python development experience in production environments. Experience working with AWS cloud services, particularly S3, Lambda, Glue, Athena, and Step Functions. Strong SQL skills and experience working with large datasets and data transformations. Experience building and maintaining data pipelines and ETL workflows. Experience working with backend APIs and cloud-based systems. Comfortable working across backend engineering, infrastructure, and data processing. Strong problem-solving skills with a pragmatic engineering mindset. Ability to take ownership of systems end-to-end, including maintenance, troubleshooting, and improvement initiatives. Comfortable operating in a fast-moving environment with evolving priorities. Experience using AI-assisted development tools such as ChatGPT, Claude, Cursor, or Copilot to improve productivity and automate workflows. Strong communication and collaboration skills. Nice to Have Experience supporting analytics dashboards or client-facing reporting platforms. Experience optimising AWS Lambda and API Gateway performance. Familiarity with serverless architecture patterns. Experience working with SFTP-based ingestion pipelines. Exposure to modern frontend technologies and dashboard tooling. Experience in modernising or consolidating legacy systems. Familiarity with automotive, insurance, telematics, or analytics-related data platforms. Experience improving observability, monitoring, and operational reliability across cloud systems. Benefits Fixed Shifts: 12:00 PM - 9:30 PM IST (Summer) | 1:00 PM - 10:30 PM IST (Winter) No Weekend Work: Real work-life balance, not just words Day 1 Benefits: Laptop and full medical insurance provided Support That Matters: Mentorship, community, and forums where ideas are shared True Belonging: A long-term career where your contributions are valued 5-Day AI Training: Hand .
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.