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Data Engineer Microsoft Fabric / OneLake Role Overview We are looking for a Data Engineer to develop and maintain a contemporary data platform leveraging Microsoft Fabric, OneLake, and the Medallion Architecture. The role will focus on building scalable data pipelines, implementing data transformation and quality processes, and supporting curated data products for analytics and Power BI. Key Responsibilities - Develop and maintain Microsoft Fabric / OneLake Lakehouse solutions across Bronze, Silver, and Gold layers. - Build reusable data ingestion pipelines and CDC frameworks for sources including GCP, CSV, Excel, email files, and SharePoint. - Implement Bronze-layer ingestion with audit logging, schema validation, schema-drift detection, and error handling. - Develop Silver-layer transformations for cleansing, standardization, data quality, validation, and exception handling. - Build Gold-layer datasets including curated entities, conformed dimensions, business metrics, KPIs, aggregations, and secure views. - Develop and optimize Spark / PySpark, Python, and SQL workloads for scalable data processing. - Build data pipelines using Fabric Data Pipelines, Synapse Pipelines, and Notebooks. - Support Power BI semantic models and Direct Lake data consumption requirements. - Implement data quality checks, reconciliation processes, monitoring, and operational controls. - Follow data governance and security standards, including Purview, RBAC, PII/PHI controls, classification, and lineage. - Troubleshoot pipeline failures, performance issues, data discrepancies, and production incidents. - Collaborate with Solution Architects, Lead Data Engineers, BI teams, and business stakeholders to deliver scalable data solutions. Required Experience & Skills - 4+ years of overall Data Engineering experience with hands-on experience in Azure / Microsoft Fabric. - Strong hands-on experience with Microsoft Fabric Lakehouse, OneLake, Warehouse, Data Pipelines, and Notebooks. - Proficiency in Spark / PySpark, Python, SQL, and Delta Lake. - Experience with ETL/ELT, CDC, data ingestion, transformation, and Medallion Architecture. - Experience developing data quality, validation, reconciliation, and exception-handling frameworks. - Knowledge of Power BI semantic models and Direct Lake. - Experience with Microsoft Purview, Azure DevOps, Git, CI/CD, and deployment - Commercial insurance or brokerage data experience preferred. Education & Certifications - B.Tech / Bachelors degree or equivalent in Computer Science, Engineering, Information Technology, or a related field. - Microsoft Fabric or Azure Data Engineer certification preferred. .
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.