Microsoft is a company where passionate innovators come to collaborate, envision what can be, and take their careers to places they cannot achieve anywhere else. This is a world of more possibilities, more innovation, more openness, and more impact.

Commercial Engineering & AI (CEAI) partners closely with stakeholders to accelerate the transformation of Microsoft’s commercial business into a frontier organization. We bring together AI‑native engineering, modern platforms, and deep commercial insight to reimagine how work gets done - at scale and with impact. Our mission is to unlock new ways of operating through intelligent systems while creating the conditions for our teams to do the most meaningful work of their careers.

Customer Success Engineering (CSE) within the Commercial Engineering and AI (CEAI) organization builds and manages critical products and services that Microsoft runs on. We pursue big ideas that power transformational advances for Microsoft and its customers while helping teams work smarter, faster, and more securely every day.

We are looking for Sr. software engineer to work on petabyte-scale commercial data platform that turns raw operational and business signals into grounded intelligence — powering agents that help leadership and every persona make faster, better decisions. As a Software Engineer – Data, you will design and build the pipelines, curated semantic models, and agents that convert raw data from 200+ transactional sources into trusted KPIs, recommendations, and deep-linked actions across the business. You will work across the full stack of a modern data estate — from ingestion and large-scale compute, to curated logical models, to the agent orchestration layer that answers natural-language questions with facts, reasoning, and recommendations.

Responsibilities:

• Design & Build petabyte-scale data pipelines — Design, develop, and operate reliable ingestion and transformation pipelines.
• Proven ability to design system architecture for large-scale data platforms — data modeling, layering, scalability, reliability, and cost trade-offs.
• Convert raw data into intelligence — Transform staging → canonical → curated data products, building purpose-built, curated semantic/logical models.
• Mine logs to drive optimization — Instrument, collect, and analyze telemetry and operational logs to surface anomalies, root-cause trends, and process-optimization opportunities.
• Design & build agents for leadership and other personas — Develop AI-native agents that decompose natural-language questions, route them to the right domain skill, and return insights driven by reasoning, insights, and recommendations.
• Deliver KPIs that measure business outcomes — Partner with stakeholders to define, model, and ship the KPIs and persona dashboards that quantify business impact and inform executive decision-making.
• Rapidly prototype and prioritize ideas
• Good data modeling skills — dimensional/semantic modeling, schema design, normalization/denormalization trade-offs, and building reusable curated models across domains.
• Own engineering fundamentals — Enterprise-grade logging, telemetry, evaluations, regression, performance testing, security, and continuous learning across every layer of the platform.
• Advance data governance — Build with data tagging, RBAC/attribute-grained policy, lineage, audit telemetry, compliance, and data-quality standards baked in.

Tech Stack You'll Work With

Data foundation & compute

• Azure Fabric OneLake, ADLS Gen2, Azure Synapse, Azure Databricks
• Azure SQL Hyperscale, Cosmos DB
• Fabric Graph, curated semantic models (NL2SQL / NL2DAX)

Agentic & AI layer

• Agent orchestration
• Copilot Studio Flow, MCP endpoints / FastAPI web apps
• Azure AI Foundry — LLMs, SLMs, fine-tuned models; graph-powered routing and grounding

Required

• 3-5 years of software/data engineering experience building production data pipelines at scale.
• Good programming skills (e.g., Python, and/or Scala) and Good SQL.
• Hands-on experience with large-scale distributed data processing (Spark/Databricks, Synapse) and cloud data lakes (ADLS Gen2 / Fabric OneLake).
• Experience designing curated/semantic data models and delivering KPIs to business stakeholders.
• Solid grounding in data governance, security, lineage, and data quality.
• Ability to translate ambiguous business questions into robust, well-modeled data products.

Preferred

• Experience building LLM/agentic applications — orchestration, RAG/grounding, NL2SQL/NL2DAX, skill routing, or MCP-based integrations.
• Familiarity with Azure AI Foundry, Copilot Studio, and evaluation/fine-tuning workflows for agents.

How You'll Work

• Customer/stakeholder-obsessed: you partner directly with leadership and persona owners to define outcomes, then measure them with KPIs.
• Bias for action: you rapidly prototype, validate, and prioritize ideas
• Engineering excellence: you build observable, secure, high-performance systems with continuous learning and evaluation built in.
• AI-native mindset
• Design-first: you think in architecture — clear contracts, reusable models, and patterns that scale — and communicate them through crisp design docs and reviews.

#CEAIjobs

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.