About Beyond Key:
We are a Microsoft Gold Partner and a Great Place to Work-certified company. "Happy Team Members, Happy Clients" is a principle we hold dear. We are an international IT consulting and software services firm committed to providing. Cutting-edge services and products that satisfy our clients' global needs. Our company was established in 2005, and since then we've expanded our team by including more than 350+ Talented skilled software professionals. Our clients come from the United States, Canada, Europe, Australia, the Middle East, and India, and we create and design IT solutions for them. If you need any more details, you can get them at
https://www.beyondkey.com/about.
Role Summary:
This role drives
enterprise-wide business intelligence, data analytics, and AI-powered data access
by building scalable Power BI reports, maintaining the Microsoft Fabric data platform, and — critically —
developing and deploying AI data agents
that allow business users to interact with enterprise data through natural language.
AI agents are a key strategic direction for the team
, and this role will be instrumental in building that capability.
Data platform integrates sources from
D365 CRM (Dataverse)
and
Dynamics NAV (SQL — 5 databases)
through
OneLake, Data Factory orchestration, and Semantic Models with DAX calculations and row-level security (RLS)
. In 2025, the team completed the
Fabric Medallion Architecture
(covering NAV, CRM, and SafeGraph data sources through bronze, silver, and gold layers) and
rebuilt refreshable Power BI reports using Fabric Semantic models for global financial reporting
. In 2026, the focus shifts to
Power BI Report Organization & Modernization
(replacing and improving existing reports), plus a major push on
AI-Driven Innovation & Technology Leadership
— including
Copilot agents for IT
and
expanded service enhancements using AI (proactive service and analysis)
. The team has already begun
Fabric data agent testing
, narrowing focus to specific use cases like invoicing data (refreshable reports for AP and AR include posted invoices, posted payments, and total deposits, designed using data from NAV), and is actively building
specialist agents for AP (Accounts Payable) and AR (Accounts Receivable)
tasks that will be integrated into a
master agent using Copilot Studio
.
The developer will work alongside the existing Data/BI resource in India and collaborate closely with the U.S. Business Systems team to deliver reporting solutions and AI-powered analytics tools.
Key Responsibilities:
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.
Integrating specialist agents into a
master orchestrator agent using Copilot Studio
, and adding
suggested prompts
to help users query data more effectively. AI framework envisions orchestrator agents that
delegate tasks across a team of specialists
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).
Required Qualifications:
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.
Preferred Skills:
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.
Certifications:
Microsoft certifications like
Data Analyst Associate (PL-300)
,
Azure Enterprise Data Analyst (DP-500)
, or
Fabric Analytics Engineer (DP-600)
are advantageous.
