Sr Software Engineer

RESPONSIBILITIES Full Stack Development

• Collaborate with the development team to maintain, enhance, and scale the product for enterprise use.
• Design and develop scalable, high-performance solutions using cloud technologies and containerization.
• Contribute to all phases of the development lifecycle, following SOLID principles and best practices.
• Write well-designed, testable, and efficient code with a strong emphasis on Test-Driven Development (TDD), ensuring comprehensive unit, integration, and performance testing.
• Ensure software designs comply with specifications and security best practices.
• Recommend changes to improve application architecture, maintainability, and performance.
• Develop and optimize database queries using T-SQL.
• Build and maintain microservices-based architectures where applicable.
• Prepare and produce software component releases.
• Develop and execute unit, integration, and performance tests.
• Support formal testing cycles and resolve test defects.
• Enhance software efficiency, maintainability, and scalability, with a strong focus on cloud-native solutions.
  Microsoft Fabric Power BI Integration
  • Architect and implement modern reporting solutions using Power BI and Microsoft Fabric, including migration from legacy reporting platforms.
  • Design and build Power BI Embedded integration within web applications, including embed token management, authentication, and report lifecycle APIs.
  • Design enterprise-grade semantic models and data pipelines using Microsoft Fabric workloads (OneLake, Dataflows Gen2, Lakehouse, Direct Lake mode).
  • Develop advanced DAX measures, calculated columns, and time-intelligence functions to support complex reporting requirements.
  • Design and implement data ingestion pipelines from relational databases and enterprise data sources into Microsoft Fabric and semantic models.
  • Optimize Power BI report and dataset performance using Performance Analyzer, DAX Studio, and query reduction techniques.
    AI-Specific Responsibilities
    • Integrate AI-powered tools and frameworks to enhance code quality and development efficiency.
    • Utilize AI-driven analytics to identify performance bottlenecks and optimize system performance.
    • Implement AI-based security measures to proactively detect and mitigate potential threats.
    • Leverage AI for automated testing and continuous integration/continuous deployment (CI/CD) processes.
    • Guide the adoption and effective use of AI agents for automating repetitive development, deployment, and testing processes within the engineering team. ","

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