Infosys
Website:
infosys.com
Company:
https://www.linkedin.com/company/infosys
Seniority: Not Applicable
Industries: IT Services and IT Consulting
Job details:
Technology->Cloud Platform->Azure Devops,Technology->Microsoft Technologies->Microsoft Fabric
Microsoft Fabric Development Design and implement solutions using Microsoft Fabric components: OneLake Data Factory (Fabric pipelines) Data Engineering (Lakehouse, Notebooks) Data Warehousing Power BI Build and maintain Lakehouse and Warehouse architectures Data Pipeline & Integration Develop data ingestion pipelines from multiple sources (on-prem, cloud, APIs) Implement ETL/ELT workflows using Fabric Data Factory Orchestrate workloads using pipelines and triggers Data Engineering & Processing Work with Spark (PySpark/Scala) notebooks in Fabric Transform large datasets using distributed computing Manage structured and unstructured data Analytics & Reporting Integrate Power BI for data visualization and reporting Build semantic models and datasets Enable self-service BI capabilities Azure Subscription Management Deploy and manage resources within Azure subscription Handle access control (IAM), governance, and security Monitor performance and optimize costs Performance & Optimization Optimize queries and storage in Lakehouse/Warehouse Implement partitioning and data modeling strategies Ensure high performance and scalability Core Skills 3–5 years of experience in data engineering / Azure data services Hands-on experience with Microsoft Fabric (or Synapse + Data Factory equivalent) Strong SQL skills Experience with ETL/ELT pipelines Fabric / Azure Stack Microsoft Fabric Azure Data Factory (or Fabric Pipelines) Azure Synapse Analytics Data Lake (ADLS Gen2 / OneLake) Power BI Programming Proficiency in Python / PySpark / SQL Familiarity with Spark-based processing
Experience with real-time analytics or streaming (Event Hub, Kafka) Knowledge of Delta Lake / Lakehouse architecture Familiarity with CI/CD (Azure DevOps, GitHub) Microsoft Certifications (e.g., DP-600, DP-203)
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