Top Data Engineer Jobs in Chicago, IL

The Data Engineer will design and maintain data pipelines, optimize cloud data warehouses, and collaborate with analytics teams while mentoring junior staff.

Design, develop, and manage data infrastructure for internal and client projects, focusing on large-scale data pipelines, APIs, and cloud deployments.

The Data Engineer designs and manages data pipelines for lead generation, collaborates with Sales, analyzes metrics, and ensures data quality and integrity.

The Principal Data Modeler will design and manage data models for the Marketing Data Warehouse to support data-driven marketing decisions and optimize data architecture.

Design, build, and maintain scalable data pipelines and tooling to support AI and analytics. Manage datastores (MySQL, Redshift, OpenSearch), implement AWS-based ETL/ELT solutions, collaborate with data science and product teams, and ensure data quality, automation, and production reliability.

As a Data Engineer, you will build and maintain data pipelines, ensure data quality, support ML workflows, and optimize query performance using various technologies.

The Principal Data Engineer will design and maintain data systems, evaluate technology solutions, mentor team members, and communicate effectively with stakeholders.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

As a Data Engineer at Common Room, you'll build ETL pipelines, process billions of events daily, and collaborate on backend projects using AWS, Postgres, and Node.js.

As a Senior Data Engineer, you will design and optimize data pipelines for analytics, guide junior engineers, and translate business requirements into scalable data solutions.

The Data Migration Engineer migrates customer data into SaaS products, ensuring data quality and business continuity while collaborating with teams and managing customer requirements.

The Data Engineer is responsible for developing data infrastructure, building data pipelines, managing data quality, and integrating analytics tools to support design and project operations.

The Lead Data Engineer modernizes and optimizes the Medicaid Market's data platform, manages ETL processes, and partners with the Business Intelligence team to enhance data accessibility and reliability, while also leading contract resources in a complex environment.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

The Lead Data Engineer will manage U.S. Data Strategy capabilities, translating business objectives into cloud data solutions, while ensuring scalability and security. This includes ETL, analytics, and technical leadership in a hybrid work environment.

Lead design and delivery of enterprise data platforms using Snowflake and AWS. Architect ELT/CDC pipelines, implement Data Vault 2.0 and dimensional models, optimize Snowflake performance, mentor engineers, partner with stakeholders, and ensure operational reliability and observability for analytics and BI workloads.

The Junior Data Engineer will analyze data, build and maintain data pipelines, support CI/CD processes, and assist in IT modernization efforts for a Federal client.

The Senior Data Engineer will design, build, and optimize modern data platforms using Azure and Databricks, while collaborating directly with clients to fulfill their data-related needs.

As a Senior Data Engineer, you will design and maintain scalable data models, build production data pipelines, and support analytics across various business functions.

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

The Data Engineer Senior will optimize data pipelines, work within scrum teams, mentor others, and improve data quality, reliability, and governance.

Design, build, and maintain ELT pipelines and analytics-ready data models to support reporting, KPIs, and downstream ML use cases; implement data quality, optimize pipeline performance, document lineage, and ensure governance and privacy.

The Lead Data Engineer will design and architect data retrieval systems, build inference infrastructure, improve data quality, and mentor a specialized team to enhance customer success through AI integration.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.