Software Engineer - Fabric / Power BI Developer & AI Data Agent Specialist

Location: Hyderabad, India; Indore, India; Pune, India

Department: IT-Software

Experience: 2 - 4 Years

• AI Data Agent Development & Enablement (Primary Focus): Design, configure, and deploy Microsoft Fabric Data Agents — AI-powered assistants that enable natural interaction with data by allowing users to ask questions in plain English and receive structured, human-readable responses, eliminating the need to understand query languages like SQL, DAX, or KQL. Responsibilities include:
• Building and tuning specialist data agents for specific business domains (e.g., AP/AR finance agents, sales analysis agents, operational metrics agents) following the team's principle that "one agent, one job — the narrower the scope, the more reliable and trustworthy the output".
• Ensuring the underlying semantic data models (table names, relationships, measures, field descriptions) are optimized for AI agent accuracy. The team has already identified that data agent accuracy depends on the clarity of the semantic layer and the selection of appropriate tables for each use case.
• Integrating specialist agents into a master orchestrator agent using Copilot Studio and adding suggested prompts to help users query data more effectively. Agentic AI framework envisions orchestrator agents that delegate tasks across a team of specialists — one research, one drafts, one reviews — automating complex workflows end-to-end.
• Exploring Copilot in Power BI features that allow natural language data exploration, DAX measure generation, visual suggestions, and data summaries directly within the Power BI environment.
• Evaluating new Fabric AI capabilities (e.g., Data Activator for event-driven analytics, AI/ML integration) and recommending adoption strategies.
• Monitoring AI agent performance (accuracy of responses, query efficiency, user adoption) and continuously refining agent configurations. The team has encountered challenges with latency when agents scan large datasets, and has identified building aggregated tables as a strategy to improve response times.
• Building and tuning specialist data agents for specific business domains (e.g., AP/AR finance agents, sales analysis agents, operational metrics agents) following the team's principle that "one agent, one job — the narrower the scope, the more reliable and trustworthy the output".
• Ensuring the underlying semantic data models (table names, relationships, measures, field descriptions) are optimized for AI agent accuracy. The team has already identified that data agent accuracy depends on the clarity of the semantic layer and the selection of appropriate tables for each use case.

• one researches, one drafts, one reviews — automating complex workflows end-to-end.
• Exploring Copilot in Power BI features that allow natural language data exploration, DAX measure generation, visual suggestions, and data summaries directly within the Power BI environment.
• Evaluating new Fabric AI capabilities (e.g., Data Activator for event-driven analytics, AI/ML integration) and recommending adoption strategies.
• Monitoring AI agent performance (accuracy of responses, query efficiency, user adoption) and continuously refining agent configurations. The team has encountered challenges with latency when agents scan large datasets, and has identified building aggregated tables as a strategy to improve response times[1].
• Power BI Report Development: Create, enhance, and maintain a wide range of Power BI dashboards and reports across the organization (finance, operations, sales, service, etc.). Design intuitive visualizations, KPIs, and interactive elements aligned with business requirements. Ensure reports are optimized for performance through efficient DAX calculations and proper data model design. Lead the 2026 report modernization initiative to consolidate, replace, and improve existing reports.
• Data Modeling & ETL Pipelines: Develop and manage robust data models in Power BI and Fabric, defining relationships and hierarchies that accurately represent business logic. Use Power Query (M) and Microsoft Fabric Data Factory/Pipelines to perform ETL — extracting data from sources including NAV databases, CRM Dataverse, and external data — transforming and loading it into the Fabric Lakehouse/Data Warehouse for enterprise reporting. The architecture includes Notebook-based Master Full/Incremental loads for transactions, SCD Type II handling for master data, and Delta Parquet files with automatic sync. Maintain and extend the existing Fabric Medallion Architecture (Bronze/Silver/Gold layers) covering NAV, CRM, and SafeGraph data.
• Stakeholder Collaboration & Analysis: Engage with business stakeholders to understand key metrics, data requirements, and reporting pain points. Translate business questions into technical requirements and validate report accuracy against source systems (NAV, CRM). Provide user training or demonstrations for new reports and AI data agent features — helping non-technical users learn how to get insights via conversational data tools. Create documentation for data models, dashboards, and agent configurations (data dictionaries, user guides, prompt libraries).
• Data Governance & Continuous Improvement: Implement data governance and security measures in Power BI/Fabric — including row-level security (RLS), data permissions management, and compliance with data protection policies. Establish practices for source control of BI assets (using Git integrated with Power BI or Fabric). Monitor usage and performance of BI solutions and AI data agents, and continuously optimize (e.g., refining DAX formulas, improving semantic model clarity for better AI query results, scheduling refreshes during off-peak hours).

• Education: Bachelor's degree in Computer Science, Data Analytics, Information Systems, or a related field.
• Experience: Approximately 2–4 years of experience in business intelligence and data analysis with a focus on developing Power BI solutions. Hands-on experience creating Power BI reports, dashboards, and data models is required.
• Power BI Proficiency: High proficiency in Power BI Desktop and Service — capable of building complex data models with relationships, calculated columns, and measures. Strong command of DAX (Data Analysis Expressions) for advanced calculations (e.g., year-over-year growth, rolling averages, complex aggregations). Experience with Power Query for data transformation and M code.
• Data Management Skills: Solid understanding of SQL and ability to write queries to extract and manipulate data. Familiarity with data warehousing concepts (e.g., star schema design) and comfortable working with large datasets. Experience connecting Power BI to diverse data sources (SQL databases, Azure SQL, Excel files, cloud services, Dataverse).
• Microsoft Fabric / Azure Foundations: At least a basic understanding of Microsoft Fabric or Azure analytics services, including concepts like data lakes, pipelines, and lakehouses. Experience with Azure Synapse Analytics, Azure Data Factory, or Azure Data Lake translates directly to Fabric.
• AI Aptitude: Demonstrated interest in and aptitude for AI-driven data tools. At minimum, an understanding of how AI agents and large language models (LLMs) can be applied to data analysis (e.g., converting natural language to SQL/DAX queries). Willingness to rapidly learn Microsoft's AI data agent tooling (Fabric Data Agents, Copilot Studio, Copilot in Power BI) is essential, as AI agent development is a core part of this role.
• Communication & Collaboration: Excellent analytical and problem-solving skills. Strong English communication skills to interact with business stakeholders and explain complex data findings and AI capabilities in accessible terms. Must be a team player who can collaborate with colleagues across geographies.

• AI Agent & Copilot Experience (Strongly Preferred): Hands-on experience building, configuring, or managing Microsoft Fabric Data Agents, Copilot in Power BI, or similar AI/LLM-based data Q&A tools is a significant advantage. Candidates who have created or configured such AI assistants — even in development, pilot, or demo environments — will be prioritized. Experience with Copilot Studio for building and orchestrating custom agents is especially valuable given the team's plans to create specialist agents integrated into a master orchestrator.
• Advanced Fabric Capabilities: Experience with Microsoft Fabric in a production environment — using the integrated Lakehouse, Data Warehouse, or Data Engineering components (e.g., Spark notebooks, PySpark) in tandem with Power BI. Familiarity with real-time analytics or streaming data in Fabric, and any exposure to machine learning or AI models within the data pipeline.
• NLP & LLM Foundations: Familiarity with natural language processing concepts, prompt engineering, or LLM application development (e.g., using LangChain, Azure OpenAI, or ChatGPT APIs for data applications). Understanding how semantic model quality (clear naming conventions, well-defined relationships, documented measures) directly impacts AI agent accuracy and reliability.
• DevOps & BI Deployment: Experience with Power BI deployment pipelines or using source control (Git/Azure DevOps) for BI artifact version control and continuous integration.