Role: Microsoft Azure Architect – Data, AI & Integration
Employment type: Full Time / Contract
Location: Remote / Indianapolis , Iowa (Must work Eastern Time (EST/EDT) business hours)
Customer site: Able to visit the customer office in Indianapolis, IN, as needed; candidates within commuting distance preferred, as travel costs are not reimbursed
Experience: 15+ years in IT preferred (12+ minimum), including 5+ years architecting on Microsoft Azure
Reports to: VP Delivery, North America, with a dotted line to the Delivery Leader for the customer account (India)
About the role
We're hiring a hands-on Azure Architect to design and run end-to-end data engineering and AI pipelines on the Microsoft stack. You'll build AI solutions with the models and agents in Microsoft Foundry (formerly Azure AI Foundry). You'll also lead the move of data workloads from Snowflake to Azure.
You'll be the technical single point of contact (SPOC) across several Azure engagements, owning their architecture, sizing and technical decisions from start to finish.
The role also covers the application layer: the web apps, APIs and middleware that bring data and AI into business processes. You'll work directly with client stakeholders, set the architecture direction and guide engineering teams through delivery.
The role supports a customer on Eastern Time, with regular in-person sessions at their Indianapolis office. You'll report to the VP Delivery for North America and work closely with the account's delivery leadership in India.
Key responsibilities
Data engineering and pipeline architecture
Design lakehouse and data platform architectures on Microsoft Fabric, Azure Databricks, ADLS Gen2 and Azure SQL.
Build batch and streaming pipelines with Fabric Data Factory / Azure Data Factory, Event Hubs and Stream Analytics.
Set standards for data modelling, medallion layering, data quality and lineage.
Set up data governance, cataloguing and security with Microsoft Purview, Entra ID and role-based access.
AI and Microsoft Foundry
Design generative AI and ML solutions in Microsoft Foundry, covering model catalogue selection, prompt flows, agents and evaluation.
Design retrieval-augmented generation (RAG) using Azure AI Search, embeddings and vector stores.
Manage AI pipelines across their lifecycle (MLOps/LLMOps): deployment, monitoring, evaluation, cost control and versioning.
Apply Responsible AI practices: content safety, groundedness checks, access controls and audit trails.
Snowflake-to-Azure migration
Assess Snowflake estates (schemas, SQL, stored procedures, tasks, streams, data shares) and plan their move to Fabric, Databricks or Azure SQL.
Define migration patterns, data validation and reconciliation, and cut-over and rollback plans.
Size and compare cost and performance before and after migration.
Web application and integration development
Design and build web apps on Azure App Service, Azure Functions and Azure Container Apps / AKS.
Design REST and event-driven APIs, published and secured through Azure API Management.
Build middleware and integration flows with Logic Apps, Service Bus and Event Grid, connecting ERP, CRM and other enterprise systems.
Make AI capabilities available to business users through apps, APIs and Microsoft 365 / Teams integration.
Architecture governance and DevOps
Apply the Azure Well-Architected Framework and Cloud Adoption Framework.
Define infrastructure as code (Bicep, Terraform) and CI/CD on Azure DevOps or GitHub Actions.
Produce reference architectures, solution designs and architecture decision records.
Infrastructure and capacity sizing
Size and estimate Azure infrastructure for compute, storage, networking, Fabric capacity (F-SKUs), Databricks clusters, Foundry / Azure OpenAI throughput (PTU vs. pay-as-you-go) and AI Search tiers.
Build cost models and TCO comparisons using the Azure Pricing Calculator and Azure Migrate, including Snowflake-vs-Azure cost cases.
Plan capacity for scale, high availability and disaster recovery, and set up FinOps practices such as budgets, reservations and cost monitoring.
Provide effort and infrastructure estimates for proposals, SOWs and change requests.
Client and team leadership
Act as the technical SPOC for multiple Azure engagements at once, owning technical direction, escalations, risk and quality across accounts.
Lead technical discovery, solution workshops and proposal inputs with clients.
Mentor data engineers, AI engineers and developers, and review their designs and code.
Work with Microsoft account and partner teams on co-sell, funding programmes and roadmap alignment.
Coordinate with the offshore delivery team in India across time zones.
Required skills and experience
12+ years in IT, with 5+ years as a solution or cloud architect on Azure.
Has delivered enterprise data platforms using Fabric, Databricks, Synapse or Data Factory.
Has designed and deployed at least one production generative AI solution using Azure OpenAI / Microsoft Foundry, including RAG and evaluation.
Proven experience in Azure infrastructure, capacity sizing and cost estimation for enterprise data and AI workloads.
Has been the lead technical contact across several concurrent client engagements.
Strong SQL and Python, plus working knowledge of C#/.NET or Node.js / TypeScript for apps and APIs.
Hands-on with API design (REST, OpenAPI), API Management and messaging/integration patterns.
Knows Azure security, identity and networking well: Entra ID, Key Vault, private endpoints and VNets.
Experience with IaC and CI/CD pipelines.
Can explain architecture trade-offs to both technical and business audiences.
Must be authorised to work in the US or Canada without current or future visa sponsorship.
Preferred / desirable
15+ years of IT experience across data, application and integration architecture.
Microsoft certifications (strongly preferred):
Azure Solutions Architect Expert (AZ-305)
Azure AI Engineer Associate (AI-102)
Fabric Data Engineer Associate (DP-700) or Fabric Analytics Engineer Associate (DP-600)
Ex-Microsoft experience (e.g. Cloud Solution Architect, FastTrack, Microsoft Consulting / Industry Solutions), or work with Microsoft partner programmes.
Snowflake experience, especially migrating Snowflake workloads to Azure. SnowPro certification is a plus.
Supply Chain AI experience is a definite plus, for example demand forecasting, inventory optimisation, supplier risk, production planning or logistics analytics. Familiarity with SAP / ERP supply chain data is also a plus.
Free to travel, and able to attend the Indianapolis, IN customer office in person without travel reimbursement. Candidates based in or near Indianapolis preferred.
Exposure to regulated industries such as life sciences, manufacturing or healthcare (GxP or data compliance).
Experience with agentic AI frameworks: Foundry Agent Service, Semantic Kernel, AutoGen, MCP.
Experience working with global delivery models (onshore/offshore teams).
Technology stack:
Data platform: Microsoft Fabric, Azure Databricks, ADLS Gen2, Azure SQL, Synapse
Pipelines & streaming: Fabric / Azure Data Factory, Event Hubs, Stream Analytics
Apps & integration: App Service, Functions, Container Apps / AKS, API Management, Logic Apps, Service Bus, Event Grid
Infrastructure & cost: Azure Pricing Calculator, Azure Migrate, Cost Management, Azure Monitor
Governance & security: Purview, Entra ID, Key Vault, Defender for Cloud
DevOps: Azure DevOps, GitHub Actions, Bicep, Terraform
Source platform: Snowflake
Education and soft skills
Bachelor's or Master's degree in Computer Science, Engineering or a related field.
Strong stakeholder management and consulting skills.
Takes ownership and works hands-on, mentoring others as they go.
Clear written communication for architecture documents and proposals.
What success looks like (first 6–12 months)
Reference architectures for the data, AI and integration layers are in place and adopted by delivery teams.
At least one Snowflake-to-Azure migration is planned and delivered, with reconciled data and measured cost savings.
Foundry-based AI solutions are in production with evaluation, monitoring and cost controls.
Infrastructure and cost estimates for engagements land within an agreed tolerance of actual consumption.
Pre-sales has helped win new engagements, including Microsoft co-sell.
