Top Retail Data Engineering Jobs in Chicago, IL

The Knowledge Systems Architect will design systems for knowledge organization, automate documentation processes, and enhance knowledge artifact legibility to support AI effectiveness in the R&D environment.

The Data Engineer III will design, build, and optimize data pipelines and backend systems, integrating with SAP and supporting analytics applications. Responsibilities include developing ETL workflows, backend applications, and ensuring data quality.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts. Integrate data from multiple sources, ensure data quality, optimize Hadoop/HDFS workflows, collaborate with Data Science to operationalize models, and recommend tooling and system improvements.

As a Senior Data Engineer, you'll design and build data warehouse solutions, implement ETL processes, and ensure data quality. Collaborate with business users to meet analytics needs and oversee production deployments.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.

Lead architecture and implementation of scalable data systems and pipelines from ingestion to delivery. Own ambiguous, high-impact integrations, improve data quality and reliability, adopt AI-augmented engineering, mentor engineers, and collaborate with Product, ML, and customer teams to ship production solutions.

Design, build, and maintain reliable data pipelines and models using SQL, Python, and Databricks/Spark. Translate multi-source schemas into scalable data models, enforce data hygiene and privacy, add tests/documentation/lineage, and collaborate with analytics, product, marketing, and vendor teams to deliver trustworthy data for personalization and marketing.

Early member of the Data & Analytics team responsible for end-to-end analyses and data products. Build and maintain dbt models, semantic layers, and dashboards (Power BI). Partner with Finance, Merchandising, Marketing, Operations and others; own metric definitions, validate AI-generated SQL/dbt/Python, investigate data discrepancies, and help evolve Snowflake-based data infrastructure and governance.

The Data Engineer III will lead the development and maintenance of data infrastructure and tools, ensuring data integrity while driving strategic data initiatives.

As a Data Engineer, you'll design and optimize data pipelines, collaborate with teams for analytics and machine learning, and enforce data governance standards.