Top Data Architect Jobs in Chicago, IL

The Principal Data Architect will design and oversee the enterprise data architecture, ensuring effective modeling, integration, governance, and consumption of data across the organization. Responsibilities include building data models, implementing lakehouse strategies, and partnering with multiple teams for the evolution of data practices.

Develop and maintain datasets for visualization and machine learning; automate data pipelines; partner with teams to build data products.

Design and own data migration strategy and architecture. Map source-to-target data models, build data dictionaries, perform migrations and testing, reconcile results, and collaborate with stakeholders and project teams to ensure successful modernization.

Design and govern enterprise data architectures within the Informatica ecosystem. Lead data modeling, ETL/integration using Informatica tools, enforce data quality and governance, optimize performance, manage metadata and lineage, collaborate with stakeholders, document solutions, and train teams.

Lead design and implementation of scalable data architectures using Capsenta. Build and maintain data models, ontologies, and graph databases; manage databases; integrate data sources; optimize performance; enforce data governance; document solutions; collaborate with engineers and stakeholders; and stay current on semantic and knowledge-graph technologies.

Design scalable, secure data architectures on Google Cloud, lead discovery and migration from legacy systems, define ETL/ELT patterns, enforce governance and security, optimize performance, collaborate with stakeholders, and document architecture and migration progress.

Design, build, and optimize Spark ETL pipelines using Scala/Python and Oracle SQL. Lead and mentor a team of engineers, collaborate with stakeholders on scalable data solutions, ensure data integrity, security, and performance, and stay current on emerging technologies to drive improvements.

Lead architect to design and implement large-scale, distributed big data solutions using Java and Big Data technologies. Hands-on with Java 1.8+, Apache Spark, MapReduce, Hadoop/Cloudera, Hive, Impala, YARN, and Kafka. Perform data analysis, design scalable architectures, enforce testing (JUnit), and optionally use Unix/Python scripting. Manage global technology teams, apply industry best practices, and communicate effectively across stakeholders.

Design and implement scalable end-to-end data architectures, including data modeling, ETL/ELT pipelines, cloud data platforms, streaming integrations, governance, security, and enablement for analytics and AI/ML. Mentor engineers and document architecture for stakeholders.

Lead database design, data modeling, schema evolution, migrations, and ETL/ELT pipelines across MySQL, PostgreSQL, and Google Cloud databases. Build streaming and batch ingestion, enable CI/CD for data deployments, troubleshoot pipelines, produce runbooks, and mentor/lead offshore DB/ETL engineers while collaborating with onshore architects.

Design and maintain enterprise data architecture and lakehouse solutions. Lead data migration, integration, governance, and BI enablement. Define strategy, implement pipelines, ensure data quality, security, and provide technical leadership and mentoring.

As a Data Architect, you will define and implement data architecture solutions, collaborate with stakeholders, and design data platforms and pipelines to enhance data management and analytics capabilities.

The Data Architect will design scalable data solutions, enforce data standards, lead architecture discussions, and collaborate with stakeholders. Responsibilities include managing platforms, ensuring data compliance, optimizing pipelines, and guiding teams toward data-driven solutions.

Design and advance enterprise data and BI architecture: optimize OLTP/OLAP models, establish modeling/integration/governance standards, lead POCs, mentor teams, enable AI/ML, and guide cross-functional implementation from concept to production.

Lead definition and evolution of cloud data architecture and analytics platform using a lakehouse approach. Design secure, scalable AWS data platforms, medallion data layers, data modeling standards, ETL/ELT and streaming pipelines, governance, observability, and AI/ML enablement. Drive tool selection, cross-team architecture reviews, mentor engineers, and enforce data security, compliance, and operational excellence across the organization.

The Data Architect/Data Governance Lead supports the Medicaid Enterprise Data Warehouse by leading data architecture, metadata management, and governance processes, ensuring compliance and scalability.

Responsible for developing enterprise architecture and modern data platforms, ensuring data governance, quality, security and supporting data-related initiatives across the organization.

Support to evaluate and implement scalable data infrastructure. Work with technical teams to optimize data delivery and build reliable data systems. Expertise in data modeling, integration patterns, and data quality assurance is essential.

The Senior Data Solutions Architect designs data solutions to align with business strategy and architecture, ensuring data integration and governance across enterprise platforms.

Design and implement enterprise data architectures and lakehouse/warehouse solutions using Microsoft Fabric, Databricks or similar platforms. Lead data modeling, ETL/ELT pipelines, cloud integration, CI/CD, and stakeholder-facing consulting engagements to deliver scalable, secure analytics systems.

Own and implement the canonical data model and governance for a multi-tenant MEP SaaS platform. Architect data for AI/ML readiness (RAG, embeddings, vector search), design polyglot persistence and lake/lakehouse pipelines, lead staged modernization and migrations, produce hands-on prototypes and in-repo guardrails, and partner with platform, DB engineering, and ML teams to ensure data quality, lineage, and observability.

Design, support, and improve data analytics solutions (OAC and Power BI). Manage data ingestion, ETL, data quality, access, and documentation. Liaise with stakeholders, migrate dashboards from OAC to Power BI, and follow SDLC and project management practices.

Design and govern enterprise data and analytics architectures, define integration patterns, evaluate platform capabilities, provide technical leadership and architectural reviews, manage technology risks, and support implementation teams to deliver secure, scalable, cost-effective data solutions aligned with enterprise standards.

The role involves acting as a subject matter expert in Data and AI, providing technical expertise during sales processes for Azure-based solutions, and mentoring team members to enhance client experiences.

Design and deliver Databricks-centric data architectures, lead pre-sales and billable engagements, build end-to-end data engineering pipelines for AI/ML and BI, mentor teams, ensure data governance/security/quality, and resolve data system issues while producing solution documentation and presentations.