Senior Ai Analytics Engineer Fabric Iq

Must Have Technical/Functional Skills

* 8+ years of experience in software engineering, analytics, business intelligence, or AI application development.

* Hands-on experience with Microsoft Fabric, including OneLake, Lakehouse or Warehouse, Power BI semantic models, and Power BI Embedded.

* Working knowledge of Fabric IQ concepts, including ontologies, business entities, relationships, graph-based context, and agent-ready semantic layers.

* Strong experience developing modern web applications using React 18.x or 19.x, TypeScript, JavaScript, reusable UI components, and REST APIs.

* Experience building AI-led reports and AI-embedded analytics, including natural-language interaction, automated narratives, anomaly or trend explanations, recommendations, and conversational analytics.

* Hands-on experience with Azure OpenAI or comparable large language model services, prompt engineering, retrieval-augmented generation, semantic search, and AI evaluation.

* Strong understanding of report discovery, persona and use-case analysis, KPI definition, data lineage, semantic modeling, and report rationalization.

* Ability to rapidly prototype 2 to 3 high-value reports and convert discovery findings into epics, features, user stories, acceptance criteria, estimates, dependencies, and a prioritized backlog.

* Experience defining reusable architecture patterns, report templates, React components, prompt libraries, semantic models, and governance controls for enterprise-scale adoption.

* Strong SQL skills; proficiency in Python or C# is preferred. Experience integrating structured and unstructured enterprise data is desirable.

* Excellent facilitation, stakeholder management, communication, and storytelling skills for both technical and executive audiences.

Roles & Responsibilities

* Lead discovery workshops with business, product, data, UX, security, and technology stakeholders to understand current reports, decisions supported, user journeys, pain points, KPIs, data sources, and regulatory constraints.

* Assess the existing reporting landscape and classify reports for modernization, consolidation, redesign, reuse, or retirement using agreed business-value, complexity, risk, and usage criteria.

* Select and develop an initial set of 2 to 3 representative AI-powered report prototypes that demonstrate measurable business value and establish reusable implementation patterns.

* Design AI-led reports that proactively surface insights, drivers, trends, exceptions, contextual narratives, and recommended next actions instead of presenting static metrics alone.

* Build AI-embedded report experiences in React and Power BI Embedded, including conversational interfaces, natural-language exploration, guided analysis, explainable insights, and role-aware experiences.

* Develop and align Fabric IQ ontologies, Power BI semantic models, business definitions, relationships, rules, and actions so reports and AI agents use consistent enterprise context.

* Integrate enterprise data from Microsoft Fabric, APIs, lakehouse or warehouse platforms, operational systems, documents, and approved knowledge sources while maintaining security and lineage.

* Validate prototypes with end users through demonstrations and structured feedback; document business outcomes, functional gaps, technical constraints, adoption considerations, and lessons learned.

* Translate discovery and prototype findings into a delivery-ready backlog containing epics, capabilities, featu res, user stories, acceptance criteria, technical enablers, non-functional requirements, dependencies, risks, and prioritization rationale.

* Define the roadmap and scalable delivery approach for expanding from the initial prototypes to an approximately 3,000-report estate, including waves, report archetypes, reusable accelerators, automation opportunities, quality gates, and governance.

* Establish development standards for React components, embedded analytics, prompts, semantic models, AI evaluation, accessibility, observability, testing, deployment, and responsible AI.

* Collaborate with product owners and delivery teams on planning, estimation, release sequencing, sprint execution, demos, documentation, and knowledge transfer.

* Measure outcomes such as adoption, decision-cycle improvement, report consolidation, insight quality, response accuracy, performance, and reuse of common assets.

Salary Range: $110,000-$130,000 a year

TCS Employee Benefits Summary:

Discretionary Annual Incentive.

Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.

Family Support: Maternal & Parental Leaves.

Insurance Options: Auto & Home Insurance, Identity Theft Protection.

Convenience & Professional Growth: Commuter Benefits & Certification & amp; Training Reimbursement.

Time Off: Vacation, Time Off, Sick Leave & Holidays.

Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

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Desired Candidate Profile