Top Data Engineer Jobs in Chicago, IL

Build and operate cloud data capabilities, including ingestion pipelines, transformations, data models, curated data products, and data-quality controls. Use Snowflake, dbt, SQL, and Python to deliver governed data for analytics, applications, automation, and AI workflows. Implement testing, CI/CD, documentation, lineage, access controls, monitoring, incident resolution, and performance optimization. Collaborate with engineering, analytics, governance, security, and business teams in an Agile, product-oriented environment with active AI-assisted development.

Design and operate scalable, cloud-native data pipelines and orchestration systems for imaging, biomarker, and healthcare data. Build Databricks and distributed processing workflows, integrate DICOM data into data lakes, and implement validation, observability, monitoring, and fault tolerance. Collaborate with data science, AI, R&D, product, and data management teams to deliver secure, compliant, reliable data for analytics and machine learning.

Belvedere Trading seeks a Senior Data Engineer to enhance trading performance through data availability and reliability, designing ETL pipelines and data architectures in a fast-paced environment.

Own and maintain the companys data infrastructure and pipelines. Design, build, and monitor ETL/ELT workflows and data architecture; integrate SaaS sources; enforce data quality, standards, and governance; partner with stakeholders to deliver analytics-ready data and meet data availability SLAs.

Designs and operates an AWS-native lakehouse supporting analytics, reporting, visualization, and AI/ML. Builds batch and streaming ingestion pipelines using Python and PySpark, Apache Iceberg data structures, governance and metadata services, quality controls, security, observability, and CI/CD automation. Optimizes performance, scalability, reliability, and cost while collaborating with cross-functional technical teams and documenting architecture, operations, and secure configurations.

Designs, builds, and optimizes modern Azure and Databricks data platforms for clients. Responsibilities include client discovery, requirements workshops, architecture discussions, batch and streaming ingestion, lakehouse and dimensional modeling, data transformation, governance, monitoring, DevOps, security, and solution reviews. The role also communicates recommendations to technical stakeholders and leadership while delivering scalable analytics and reporting solutions.

Designs and maintains data warehouses, semantic models, metrics layers, pipelines, dashboards, and certified datasets. Establishes KPI governance, data security, row-level access controls, quality standards, and observability. Builds Sigma, Power BI, and Databricks dashboards, supports self-service analytics, resolves BI issues, and enables AI/ML use cases. Collaborates with architecture, engineering, analysts, and business stakeholders to define requirements, document solutions, train users, and drive BI adoption.

The role involves building and maintaining AI data capabilities, implementing data pipelines, and ensuring operational excellence in data management within a healthcare context.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Lead and mentor a data engineering team to design, develop, test, and support cloud-based big data and streaming solutions. Build full-stack data pipelines using Java/Scala/Python, RDBMS/NoSQL, Redshift/Snowflake, and cloud platforms. Collaborate with product managers, perform unit tests and code reviews, and promote engineering best practices and tech community engagement.

The Cloud Data Engineer designs and supports scalable Snowflake and Azure data architectures, environments, and ETL/ELT pipelines. Responsibilities include Snowflake performance and cost optimization, Azure resource management, security controls, troubleshooting, documentation, design reviews, and collaboration with architecture, engineering, BI, and security teams. The role also contributes to software development, testing, debugging, mentoring, and data warehouse and data mart implementation.

Build, deploy, and operate production-grade data pipelines and data products for healthcare audiences. Design transformations, data models, and governed views using Python, SQL, Airflow, S3, Snowflake, and EMR. Implement data-quality, monitoring, and privacy-by-design controls for PHI/PII. Partner with product, analytics, and platform teams to onboard sources, support audience discovery, segmentation, activation, measurement, and troubleshoot production issues.

Build, optimize, and maintain data pipelines, ETL processes, data architectures, AI solutions, and analytics platforms. Develop cloud-based solutions using Azure Functions and containerization, implement CI/CD workflows, integrate databases and APIs, and ensure data quality, monitoring, reliability, and documentation. Troubleshoot production issues, collaborate with cross-functional teams, and apply modern data engineering, AI, cloud, and DevOps practices.

Build modern data and AI analytics solutions using ThoughtSpot, Snowflake, semantic data layers, and governed data assets. Develop ETL processes, AI prompts, intelligent dashboards, and interactive analytics experiences for actuarial teams. Partner with business and analytics stakeholders to support pricing, reserving, underwriting, and portfolio decisions while surfacing trends, explaining business drivers, and enabling actionable recommendations.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

Lead design and scaling of the data platform and analytics pipelines. Build and maintain ETL/ELT workflows, integrations, serverless data services, and reliable data models. Mentor teammates, improve automation, observability, and data governance to support analytics and operational insights.

Lead a team of engineers to design and implement data solutions using cloud technologies, optimizing data pipelines and collaborating with Agile teams to deliver impactful data-driven products.

Lead and mentor data engineering teams to design, build, test, and support cloud-based, full-stack data solutions. Work with big data, streaming, and data warehousing technologies (Redshift/Snowflake), collaborate with product managers, and ensure high-quality, performant code and systems.

Lead Data Engineer designs, develops, tests, and supports cloud-based data solutions. Collaborates with Agile teams, mentors engineers, implements big data and streaming systems, and optimizes code for performance to deliver data-driven products.

Design, build, and maintain scalable batch and real-time data pipelines and data lake architecture. Improve observability and SLOs, optimize ETL/ELT, develop dbt workflows, support event-driven architectures, integrate financial APIs, and collaborate with analytics and ML teams to deliver reliable, model-ready data products.

Designs, builds, and maintains scalable data pipelines, data marts, enterprise data platforms, and ETL processes. Integrates diverse data sources, improves data quality and performance, and supports secure analytics infrastructure using Microsoft Fabric and Azure. Develops Tableau and Power BI dashboards, collaborates with cybersecurity and cross-functional teams, manages project deliverables, documents processes, and trains team members on data organization and interpretation.

Own and evolve the data infrastructure powering identity and fraud products. Build and operate scalable ETL/ELT pipelines, ensure data quality and observability, optimize storage and access, support product squads, respond to production incidents, mentor engineers, and drive data platform innovation.

Lead the Data Platform Engineering team owning ETL/reverse-ETL pipelines, replication, and production datastores. Define architecture, roadmap, standards (IaC, observability, schema contracts), mentor engineers, drive incident response and durable fixes, and partner on cross-team technical decisions and operational reliability for data correctness, completeness, and timeliness.

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.

Designs and maintains healthcare data pipelines, ETL workflows, databases, data models, and analytical frameworks. Analyzes claims and payer data to identify trends and insights, while ensuring data quality and integrity. Creates reports, dashboards, and visualizations for nontechnical stakeholders and collaborates with healthcare policy experts, analysts, and other stakeholders to translate requirements into data solutions. The role also improves data infrastructure and analytics capabilities.