HomeData ArchitectChicago

Data Architect
Chicago.

Former Microsoft data architects working with Chicago and Midwest enterprise teams. Azure data platform design and delivery, data governance, semantic layer architecture, and AI-ready data foundations.

Get Your Data Architecture Audit →

Chicago Data Landscape

Why Chicago enterprise organisations need senior data architecture expertise.

Chicago's economy spans financial trading infrastructure, healthcare networks, logistics operations, and manufacturing — each sector generating distinct data architecture challenges at enterprise scale. The city's organisations have invested heavily in cloud infrastructure and analytics tooling. The common problem is that these investments were made incrementally without a coherent architectural framework, and the result is data environments with high maintenance burden, poor analytics trust, and growing costs.

The problems that look like BI and reporting problems in Chicago organisations are almost always data architecture problems. Inconsistent KPI definitions, slow dashboards, analysts building their own workarounds, data that engineers trust but executives don't — these are symptoms of an architecture that was built for a smaller organisation and never redesigned as the business grew.

What We Deliver

Data architecture services for Chicago enterprise teams.

Data Architecture Assessment

A structured review of your current data environment — platform architecture, pipeline design, governance model, data quality, and BI layer. We identify the root causes of performance, reliability, and cost problems and produce a prioritised roadmap. Most Chicago organisations have problems that look like BI or reporting issues but are actually data architecture issues.

$15,000–$35,000 — 2–3 weeks

Azure Data Platform Design & Build

End-to-end design and delivery of Azure data platforms for Chicago enterprise organisations. Medallion architecture on Azure Data Lake Storage, Azure Databricks, dbt, Azure Synapse, or Fabric — sized and structured to support your analytics, reporting, and AI requirements. We build for the scale you will need in three years, not just what you need today.

8–20 weeks depending on scope

Data Governance & Compliance

Data governance frameworks for Chicago financial services, healthcare, and regulated organisations. Unity Catalog governance on Databricks, Azure Purview for data cataloguing, access control design, data lineage, and policy enforcement. We design governance models that are maintainable by your team, not governance theatre that nobody actually follows.

4–10 weeks

Semantic Layer & BI Architecture

Canonical metric definition, semantic layer design, and BI architecture for organisations where the same number appears with different values in different reports. We fix the root cause — metric definition and semantic layer — not just the dashboard symptoms. Works with Tableau, Power BI, Looker, and custom BI implementations.

3–8 weeks

AI-Ready Data Foundation

Enterprise data architecture designed to support AI and ML workloads — medallion architecture, data quality frameworks, feature store design, and retrieval infrastructure for RAG systems. Most Chicago enterprise AI pilots fail because the data foundation is not ready for inference. We build the foundation that makes AI production-viable.

Assessment + delivery: 8–16 weeks

Data Platform Modernisation

Migration from legacy on-premise data warehouses to modern cloud-native platforms. We assess, plan, and execute migrations from SQL Server DW, Teradata, and Oracle to Azure — with minimal disruption to existing reporting and analytics operations.

Scoped per engagement

Common Questions

Data architecture consulting in Chicago — frequently asked.

What data architecture problems are most common in Chicago enterprise organisations?

The most common pattern we see in Chicago: data infrastructure built incrementally over several years without a coherent architecture — multiple data warehouses, inconsistent metric definitions, no data governance, and a reporting layer that analysts have stopped trusting. Financial services firms additionally face regulatory compliance requirements (OCC, Federal Reserve, CFTC) that create specific data lineage and auditability requirements. Healthcare organisations face HIPAA compliance and clinical data governance requirements. Manufacturing and logistics organisations face the challenge of connecting operational data from plant systems with enterprise financial and reporting data.

Do you work with Chicago financial services firms? Do you understand regulatory data requirements?

Yes. We work with financial services organisations across trading firms, commercial banks, insurance companies, and asset managers. Chicago's financial sector — including CME Group members, commodity trading firms, and regional banks — has specific regulatory data requirements under CFTC, OCC, and Federal Reserve guidance. We design data platforms and governance frameworks that support regulatory reporting obligations, not just operational analytics.

How much does data architecture consulting cost in Chicago?

Data architecture assessment engagements (identifying problems, mapping the current state, producing a remediation roadmap) typically run $15,000–$35,000 for a mid-market organisation. A full Azure data platform build runs $80,000–$250,000 depending on scope. Ongoing advisory and architecture governance typically runs $8,000–$20,000 per month. We scope all engagements after an initial discovery call and provide fixed-price proposals where scope is clear.

We are on Azure. Is Azure the right platform for our data architecture?

For most Chicago enterprise organisations already invested in Azure, building on the Azure data stack is the right call — Azure Data Lake Storage, Databricks, Synapse Analytics, Azure Data Factory, and Microsoft Fabric create a coherent platform that integrates with your existing Microsoft footprint. That said, multi-cloud architectures (Azure + Snowflake, for example) are common where specific capabilities require it. We work across Azure, Databricks/Snowflake combinations, and pure cloud-native architectures — and we will tell you what is right for your situation.

Our executive team wants to invest in AI. What data architecture work is needed to make that viable?

Most enterprise AI initiatives stall because the data foundation is not ready. The specific gaps vary by use case, but common requirements for production AI include clean, governed, high-quality training and inference data; a semantic layer that AI systems can query reliably; feature engineering infrastructure; and retrieval infrastructure for RAG-based applications. We run AI data readiness assessments that identify exactly what is blocking your AI roadmap and what it would take to fix it.

Do you do one-off assessments or only ongoing engagements?

Both. We do fixed-scope assessments (typically 2–4 weeks) that produce a prioritised roadmap without any obligation to proceed to delivery. Many Chicago clients use the assessment to build an internal business case for a larger engagement. We also do ongoing advisory retainers for organisations that need architecture governance and guidance without a full build engagement.

Data Architecture Consulting Across the US & Australia

Data Architect New YorkData Architect Los AngelesData Architect DallasData Architect HoustonData Architect AtlantaData Architect AustinData Architect SydneyData Architect MelbourneTableau Consultant Chicago

Get your data architecture audit.

Book a 30-minute scoping call. We will assess your current data environment and tell you exactly what is causing the problems you are experiencing.

Book Your Audit →