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We are looking for a Microsoft Fabric Data Engineer (7+ years in that space) to lead the design and development of a scalable, cloud-native data platform on Microsoft Azure. The role involves integrating data from multiple enterprise systems including SAP BW, SAP HANA, Labware, ELN, Salesforce, and others to build a unified and intelligent enterprise data ecosystem. The data to be processed spans diverse business domains such as Sales, R&I;, HR, and finance, enabling cross-functional analytics and AI-driven insights across the organization. The Data Engineer will own the complete lifecycle of data ingestion, transformation, and modeling building robust, containerized, and automated pipelines using Azure Functions, Docker Containers, MS Fabric, and Kafka. This position requires a proactive mindset, strong technical depth, and the ability to deliver reliable, high-quality data solutions independently. Goals and Deliverables The primary objective is to create a unified and governed Azure-based data ecosystem that enables real-time, scalable, and trusted analytics across multiple business domains. Timezone: CET Hybrid working mode - 3 days / week in office Location: Koregaon Park Pune Goals and deliverables Goals and deliverables Key Goals and Deliverables - End-to-End Data Integration: Design and implement automated data pipelines integrating 10+ enterprise systems (SAP BW, SAP HANA, Labware, ELN, Salesforce, etc.) using Azure Functions, Docker Containers, and MS Fabric. - Data Modeling and Transformation: Develop effective data models across diverse domains sales, operations, HR, customers, materials, and finance to support analytics and AI-driven insights. - Governance, Security, and Performance: Implement strong data governance frameworks, ensure data lineage and access control, and optimize pipeline performance using Azure-native capabilities. - AI and Analytics Enablement: Deliver clean, structured, and enriched datasets ready for consumption by BI and AI/ML models for advanced analytics and KPI prediction. - Documentation and Knowledge Transfer: Prepare technical documentation, architecture diagrams, and conduct handover sessions to ensure long-term sustainability and scalability. Expected Skills and Expertise - Microsoft Fabric (MS Fabric) - Python - SQL - Azure Functions - Apache Kafka - Docker Containers - Data Modeling (Dimensional & Relational) - Multi-Source Data Integration (SAP BW, SAP HANA, Labware, ELN, Salesforce, etc.) - Event-Driven Architecture and Real-Time Data Processing - Data Governance and Security - CI/CD and GitHub Ideal Candidate Profile - Proven experience in Azure Data Engineering and cloud-native data architectures. - Expertise with MS Fabric, Azure Functions, Kafka, and Docker Containers. - Solid understanding of data modeling, ETL/ELT processes, and performance tuning. - Familiarity with SAP BW, SAP DataSphere and SAP ERP data structures for effective source system integration. - Strong sense of ownership, with the ability to work independently and deliver end-to-end solutions. .
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.