Senior Engineer

1 day ago

Chennai, Tamil Nadu, India NKT Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Job Purpose:

The Senior Engineer – Data Analytics (Microsoft Fabric) is responsible for designing, developing, and managing scalable data solutions using Microsoft Fabric's integrated services, including OneLake, Data Factory, Synapse, and Power BI. This role enables end-to-end data engineering, advanced analytics, and business intelligence to support data-driven decision-making across the organization.

Key Responsibilities:

  • Design, develop, and maintain robust data pipelines and ETL processes using Fabric's Data Factory and Synapse Data Engineering capabilities.

  • Manage and optimize OneLake storage to ensure data availability, consistency, and performance.

  • Build and maintain Data Warehouses within Microsoft Fabric for enterprise-wide analytics.

  • Develop and publish interactive reports and dashboards using Power BI integrated within Fabric.

  • Collaborate with data analysts, data scientists, and business stakeholders to translate business requirements into technical solutions.

  • Implement data governance, security, and compliance best practices within Fabric.

  • Monitor and troubleshoot data workflows, ensuring high performance and data quality.

  • Leverage Fabric's Real-Time Analytics and Data Activator for streaming or near-real-time insights where needed.

  • Stay updated with Microsoft Fabric enhancements, features, and best practices; share knowledge with the team.

  • Support training and enablement of other data professionals on Fabric.

Required Skills & Qualifications:

  • Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or related field.

  • 5+ years of experience in data engineering, data analytics, or BI roles.

  • Strong hands-on experience with Microsoft Fabric or related tools (Azure Synapse, Data Factory, Power BI, Delta Lake, OneLake).

  • Expertise in designing and developing ETL pipelines, data models, and data warehouses.

  • Proficiency in SQL, Python, PySpark, or other relevant scripting languages.

  • Solid understanding of data governance, security, and privacy principles.

  • Strong troubleshooting and performance tuning skills for big data and analytics workloads.

  • Excellent collaboration and communication skills.

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