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SOTI is committed to providing its employees with endless possibilities; learning new things, working with the latest technologies and making a difference in the world. Key Responsibilities Design, build, and maintain production grade ETL/ELT pipelines using SQL, Python, PySpark, and Spark SQL. Own end to end data pipelines from ingestion through curated, analytics ready datasets. Maintain and enhance existing integrations to ensure stability, performance, and scalability. Troubleshoot complex pipeline failures and act as a key escalation point for production support. Collaborate with Lead Engineers and Data Architects on on-prem to cloud migration initiatives. Assess legacy pipelines and integrations, contributing to migration sequencing, refactoring, and risk mitigation. Ensure continuity of business-critical data flows during phased migrations and platform transitions. Build and operate solutions across hybrid data platforms, including SQL Server, Azure Synapse, and Microsoft Fabric. Develop and maintain Fabric Lakehouses, Warehouses, Pipelines, and Notebooks aligned with architectural standards. Optimize workloads for performance, reliability, and cost efficiency. Implement data validation, reconciliation, monitoring, logging, and alerting to ensure trusted data products. Apply disciplined engineering practices: version control, CI/CD, testing, and documentation. Improve the operational maturity and production readiness of data solutions. Mentor junior data engineers through code reviews, guidance, and best practice sharing. Promote consistent engineering standards and support team onboarding. Collaborate closely with BI teams, data owners, and governance stakeholders to ensure alignment with analytics needs. Identify and drive improvements in pipeline efficiency, migration effectiveness, and developer productivity. Required Qualifications 7+ years of experience in Data Engineering, Analytics Engineering, or a related technical role. Strong hands‑on experience with SQL, Python, PySpark, and Spark SQL in distributed data environments. Proven experience building and supporting enterprise‑scale ETL/ELT pipelines in the cloud. Strong experience with Azure‑based data platforms, including Azure Synapse Analytics and/or Microsoft Fabric. Solid understanding of cloud‑native data architectures, analytics engineering patterns, and medallion architectures. Experience with Git‑based source control, CI/CD pipelines, and automated testing for data platforms. Strong problem‑solving skills and experience supporting mission‑critical production data systems. Proven ability to collaborate across engineering and business teams and mentor junior engineers. Preferred / Nice To Have Hands‑on experience with Microsoft Fabric Lakehouse and Spark workloads Experience with Azure Data Factory, Fabric Pipelines, or orchestration tools Familiarity with data governance, lineage, and certification in cloud platforms Relevant certifications such as: Microsoft Certified: Azure Data Engineer Associate, Microsoft Fabric Analytics Engineer SOTI does not charge any fees at any stage of the recruitment process. You can verify the authenticity of any SOTI job opportunities by visiting SOTI Careers . SOTI shall not be liable for any fraudulent recruitment activities carried out by unauthorized individuals or organizations. If you want to bring your ideas to life, apply at SOTI today. Please note that SOTI does not accept unsolicited resumes from recruiters or employment agencies. In the absence of a signed Services Agreement with agency/recruiter, SOTI will not consider or agree to payment of any referral compensation or recruiter fee.
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.