Top Data Architect Jobs in Chicago, IL

Lead enterprise data architecture across warehouses, data lakes, downstream applications, and AI workloads. Design data models, Medallion Architecture, ELT standards, semantic layers, APIs, access controls, and reusable datasets. Partner with business and BI teams to drive adoption, conduct architecture reviews, establish platform standards, and mentor data and analytics engineers. The role requires deep Snowflake, dbt, data modeling, pipeline, and semantic-layer expertise, with experience in AI data patterns and cloud infrastructure preferred.

Leads the design and modernization of scalable data architecture for economic data platforms, including massive time-series datasets, archival documents, and research publications. Responsibilities include data modeling, metadata and governance design, storage and processing architecture, indexing, discoverability, security, lifecycle management, and API data access optimization. Partners with application architecture and cross-functional teams to deliver highly available, secure, public-facing data platforms supporting analytics and research.

Lead data architecture and governance across Corporate Technology by developing conceptual, logical, and physical models; establishing information architecture standards; implementing data risk controls; and advancing lineage, quality, metadata, retention, localization, and tiering practices. The role partners with senior stakeholders, supports audits and control reviews, promotes Data Mesh-aligned data products, automates governance controls, and mentors architects and developers.

Lead architecture and modernization of Channels Data Platforms, migrating legacy on‑prem and mainframe systems to cloud native stacks (Azure, Databricks, Snowflake, Kafka). Define target architecture, roadmaps, operating models, NFRs, CI/CD, IaC, observability, and governance. Provide technical oversight for Payment Tracker, mentor engineers, run R&D/POCs, and deliver enterprise alignment in a regulated environment.

Leads enterprise data warehouse, reporting, analytics, and transaction-processing architecture and modernization. Designs scalable on-premises and cloud solutions, modernizes ETL and SQL into Python automation, oversees BI delivery, and establishes DevOps and CI/CD practices. Provides hands-on technical leadership across development, testing, deployment, performance, security, and support. Leads proof-of-concepts, produces architecture documentation, presents recommendations, and mentors architects, engineers, developers, analysts, and testers.

Design and govern end-to-end data architecture for an integrated supply-chain e-commerce platform: create data models, build scalable ETL/ELT pipelines, ensure GDPR-compliant data governance, enable real-time analytics, optimize databases, plan retention/archival, and prepare data for LLM fine-tuning and RAG use cases.

Designs and oversees enterprise data architectures spanning databases, warehouses, lakes, integrations, and cloud environments. Translates business requirements into scalable, secure, and cost-efficient solutions; establishes data modeling, governance, quality, metadata, and security practices; guides engineers and analysts; optimizes infrastructure; and maintains architecture documentation. Requires extensive Databricks, data engineering, big data, cloud, and stakeholder leadership experience.

Leads the architecture, design, and implementation of scalable GCP and Databricks data lakehouse platforms. Designs real-time and batch pipelines, data models, governance, cataloging, security, and performance optimization. Advises clients, translates business requirements into technical solutions, leads project teams, mentors engineers, reviews architectures, and balances strategic planning with hands-on proof-of-concept and troubleshooting work.

Designs and maintains enterprise data architecture, including data lakes, warehouses, integrations, migrations, orchestration, and data management protocols. Partners with architects, DBAs, BI teams, product leaders, and business stakeholders to support analytics and data science. Requires deep experience with cloud data environments, Azure SQL, Microsoft Fabric, Spark, Hadoop, PySpark, SparkSQL, security protocols, and enterprise data integrations.

Leads enterprise data architecture and AI/BI consumption strategy. Designs semantic layers, ontologies, knowledge graphs, analytical models, and cloud-native Databricks solutions across Azure and AWS. Builds reliable Text-to-SQL and RAG agents, establishes architecture standards and governance, evaluates agentic AI solutions, and partners with product, platform, engineering, and business teams. Mentors technical leaders, leads architecture reviews, and drives adoption of scalable, secure, AI-first data consumption patterns.

Designs and leads scalable, secure, and cost-efficient Snowflake data platforms supporting enterprise analytics, operational reporting, and generative AI applications. Serves as the technical authority for data architecture, modeling, lakehouse design, Snowflake services, dbt transformation frameworks, and Python/Snowpark development. Provides hands-on architectural leadership while influencing executive-level technology strategy.

Designs and oversees organizational data architecture and conceptual, logical, and physical data models. Translates business requirements into scalable data solutions, develops data flows and modeling standards, maintains metadata and documentation, evaluates databases for discrepancies, and identifies model reuse opportunities. Partners with application development teams and provides executive guidance on high-impact data initiatives aligned with organizational goals.

Own university data integrations from source discovery through validated, signed-off feeds. Build SQL queries and scheduled extracts, model data, support partner upgrades and migrations, translate institutional policies into accurate data feeds, and improve monitoring, documentation, and reusable integration patterns. Collaborate with registrars and database administrators while supporting a named set of university partners. The role requires deep experience with student information systems, including PeopleSoft, and occasional travel for partner onsite engagements.

Lead design and delivery of scalable data infrastructure and pipelines for PwC Tax practice. Oversee data integration, transformation, validation, security, and compliance; drive innovation, client relationships, business development, mentorship, and strategic direction across multiple projects.

Designs and implements the data architecture supporting engineering technology, analytics, automation, and AI. Assesses current systems, defines target architecture and governance, develops data models and ETL/ELT pipelines, integrates engineering platforms, and establishes metadata, lineage, stewardship, access, and quality standards. Partners with engineering and Digital Engineering teams to deliver reusable data assets, dashboards, and analytics solutions while coordinating data protection, platform evaluations, roadmaps, and stakeholder communication.

Designs modern enterprise data architectures aligned with client business goals. Leads data integration, governance, quality, storage, modeling, and delivery strategies across cloud and on-premises environments. Evaluates architectural options, advises executives, leads engineering teams, mentors talent, drives emerging technology adoption, and supports consulting business development through solution design and work estimation.

Lead and own end-to-end delivery of enterprise Data & AI programs, define data strategy and architecture (lakehouse/warehouse), drive modernization, governance, data quality, metadata/lineage, and AI adoption. Manage client relationships, account growth, program budgets, delivery teams, and stakeholder communications to ensure on-time, on-budget outcomes.

Designs and leads enterprise data architecture and strategy for an asset management business. Responsibilities include defining roadmaps, data platforms, architecture patterns, database models, data warehouses, data acquisition and distribution processes, governance, security, and AI solutions. The role requires hands-on prototyping with Snowflake, Azure, Databricks, SQL, and Python, while collaborating with global teams and influencing stakeholders across business and technology functions.

Leads technical delivery of Master Data Management solutions using Informatica MDM and PowerCenter. Designs and implements ETL mappings, workflows, transformations, data quality processes, governance practices, SQL data marts, and Python automation. Oversees MDM specialists, monitors production jobs, troubleshoots operational issues, supports testing and validation, tunes performance, documents technical solutions, and collaborates with state agencies, QA, business teams, and project leadership.

Design and own an event-driven data architecture that moves healthcare claims data through AWS and Snowflake into fraud, waste, and abuse alerts. Establish architecture standards, approve material changes, build complex pipeline components, and ensure scalability, reliability, and compliance with PII/PHI constraints. Collaborate with data science, compliance, technical, and investigative teams while supporting government review timelines. This is a hands-on principal role requiring strong Python, SQL, AWS, Snowflake, and production streaming pipeline experience.

Leads architecture for low-latency, stateful streaming systems processing high-volume sensor data. Designs ingestion pipelines, schema registries, event-driven models, data governance, lineage, fault tolerance, real-time ML integration, in-stream anonymization, and geospatial data flows. Ensures compliance with CJIS, FIPS 140-3, and FedRAMP High while mentoring engineering teams and collaborating across product, infrastructure, DevSecOps, data science, and backend functions.

Designs and supports scalable cloud data warehouses for CMS healthcare fraud, waste, and abuse analytics. Responsibilities include data modeling, healthcare interoperability, secure HIPAA-compliant governance, lineage, testing, CI/CD, automation, workflow scheduling, and technical architecture. The role integrates claims and healthcare domains using Snowflake and industry standards while collaborating with stakeholders, documenting solutions, and leading warehouse project delivery.

Lead enterprise data architecture across AWS and Databricks Lakehouse: design scalable data models, ensure governance and data quality, mentor teams, evaluate and adopt data technologies (Delta Lake, Unity Catalog), oversee large projects and deliverables, and incorporate generative AI to accelerate data modeling and delivery.

Designs and leads enterprise data architecture, including warehouses, lakes, lakehouses, data models, integration pipelines, governance, security, and analytics platforms. Partners with engineering, analytics, application, and business teams to create scalable cloud data ecosystems. Responsibilities include technology evaluation, migration and modernization strategy, architecture reviews, documentation, data quality, lineage, metadata, and technical mentorship.

Deliver customer-facing technical training in data engineering and AI through virtual and onsite sessions. Create tailored courses, projects, certifications, and assessments aligned with customer roles, tools, and business outcomes. Partner with Customer Success, Sales, Product, and Content teams to design blended learning paths, drive platform adoption, and improve measurable skills. Support diverse technical and non-technical audiences across time zones, with occasional onsite travel and success metrics tied to customer satisfaction, bookings, and professional services revenue.