Senior Business Analytics Specialist

Overview

The BI COE (Business Intelligence Center of Excellence) Platform team designs, engineers, and operates the AMP Data Platform - a centralized, enterprise-scale data platform powering business intelligence, analytics, process automation, and AI solutions across Microsoft.

Built and operated natively on Microsoft Fabric, the platform is the foundation for more than 120 semantic models, 200+ reports, numerous automation solutions, and emerging AI experiences that support over 50,000 monthly users across the Microsoft Customer and Partner Solutions (MCAPS) and Finance organizations.

As one of Microsoft's largest Fabric enterprise implementations, the platform also serves as a Customer Zero environment, partnering closely with the Microsoft Fabric Product Group to validate, influence, and scale next-generation platform capabilities.

We are on a journey to reinvent data engineering and our data platform for the age of AI - building an AI-native data platform where intelligent agents take on much of the repetitive, time-consuming data engineering work, and engineers lead with intent-first engineering: defining direction, specifications, and judgment while agents help build, test, and validate. This role is central to that shift.

We are seeking a technical Senior Business Analytics Specialist to help build and operate the next generation of Microsoft's analytics and AI platform. The successful candidate combines strong data engineering fundamentals with deep expertise in modern cloud analytics platforms, AI-native engineering practices, and enterprise-scale governance. You will work alongside Data Architect, Data engineers, BI Leads, data product owners, and product engineering teams to deliver secure, scalable, AI-ready data solutions that accelerate business impact.

This is a hands-on IC role. Every system and solution we build is secure by design - security and privacy are part of our system design from the start, not an afterthought, and AI-native engineering is core to how the team works.

Responsibilities

What Success Looks Like

In this role, you will:

* Help operate one of Microsoft's largest Microsoft Fabric enterprise platforms.

* Enable trusted data products that power analytics, automation, and AI experiences across MCAPS and Finance.

* Accelerate Microsoft's transition toward AI-native engineering through practical adoption of AI-native development practices.

* Improve platform scalability, reliability, governance, and performance for over 50,000 monthly users.

* Partner with Microsoft Fabric Product Group teams to influence and validate next-generation platform capabilities through Customer Zero adoption.

* Enable secure downstream consumption of data products and self-serve analytics - delivering governed, performant semantic models that let business users build their own analytical and AI solutions while preserving performance, security, and compliance.

* Build AI agents and AI solutions that automate repetitive, tedious data engineering and analytical tasks - freeing engineers to lead with intent-first design and accelerating the journey to AI-native data engineering.

Our Technology Environment

You will work hands-on across a modern, Fabric-native stack:

* Lakehouse & storage:
Microsoft Fabric, One Lake, Delta Lake / Parquet, Lakehouse & Warehouse, shortcuts, and medallion (bronze / silver / gold) architecture.

* Processing & compute:
Apache Spark (PySpark, Spark SQL), Fabric Notebooks, Dataflows Gen2, Data Factory pipelines, and T-SQL.

* Semantic & BI:
Power BI, Direct Lake, Direct Query and Import mode semantic models, DAX, the Verti Paq engine, and incremental refresh.

* Real-time:
Real-Time Intelligence, Eventstreams, and Eventhouse / KQL databases.

* AI & agents:
Git Hub Copilot, Copilot for Fabric, Microsoft Agency, Azure OpenAI / Azure AI Foundry, RAG, vector search, and agent frameworks.

* Governance & security:
Microsoft Purview, sensitivity labels, data lineage, RBAC, and Microsoft Entra .

* Engineering & Data Ops:
Git, Fabric deployment pipelines, CI/CD (Azure Dev Ops / Git Hub), automated data-quality testing, and observability.

* Languages:

Python, SQL / T-SQL, PySpark, DAX, and KQL.

AI-Native Data Platform Engineering

* Design, develop, and optimize enterprise-scale data pipelines, data products, and platform services on Microsoft Fabric.

* Build and maintain scalable Lakehouse, Warehouse, and Direct Lake semantic model solutions that serve analytics and AI consumption at scale.

* Use AI-native development tools and agentic workflows to accelerate delivery, testing, documentation, and operational excellence - working in an intent-first, spec-driven model where engineers define intent and approved agents help execute and validate.

* Contribute to the adoption of intelligent automation and AI-powered engineering across the platform, treating AI as a first-class engineering actor rather than an occasional tool.

Data Engineering & Analytics Enablement

* Engineer robust, idempotent ELT/ETL pipelines in PySpark,…