Top Data Engineer Jobs in Chicago, IL

The Senior Data Engineer will develop data pipelines, micro-services, and analytics products, optimize data delivery and lead integration efforts for pricing technology.

The Data Engineer Co-op will work on web data feeds, utilize AI technologies and frameworks, and develop data pipelines.

The Data Engineer will architect and deploy Big Data environments, manage data pipelines, and ensure data integrity across the organization.

The Data Engineer I will develop scalable data platform solutions, design ETL processes, optimize SQL queries, and collaborate with teams in Agile environments.

As a Data Engineer III, you will develop data solutions, lead projects, mentor peers, and ensure efficient data pipelines within cloud architectures.

The Data Engineer will design and optimize ETL jobs using PySpark, build data pipelines, and collaborate on enterprise data systems.

Develop and productionize a next-gen Dispatch System, build predictive models, automate processes, and lead a small team in optimizing operations.

The Senior Data Engineer will maintain ChowNow's data platform, enhance data pipelines, work with data scientists, and improve data quality and accessibility, contributing to executive decision-making and business growth.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

The Senior Data Engineer at Unchained will design and implement data pipelines, integrate APIs, ensure data governance, and mentor team members while focusing on accuracy and security.

Lead the evolution of SimplePractice's data stack, building scalable systems for analytics, reporting, and product insights in a fast-paced environment.

The role involves writing and deploying scripts for data collection, transforming data sets, diagnosing bugs, and collaborating with other engineers using agile principles.

The Data Engineer will design, develop, and optimize large scale data pipelines and ensure effective data delivery for cross-functional teams.

The Data Engineer at Netflix builds systems for efficient data processing and modeling, collaborating with various teams to empower analytical insights and product features.

Lead the design and development of scalable data solutions, improve Ad Relevancy, and mentor junior engineers in a collaborative environment.

Interns will support Databricks ETL framework, improve documentation, validate Metapedia, and engage in AI/ML discovery. Requires good communication and data engineering knowledge.

The Data Engineer II will design and optimize data pipelines, mentor junior engineers, and improve deployment processes to support business data needs.

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

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.

The Data Engineer will design and maintain ETL pipelines and data storage solutions, collaborating with cross-functional teams to ensure efficient data processing and delivery.

The Lead, Data Engineer leads the data engineering team, designing scalable data solutions, mentoring staff, and ensuring data quality while collaborating with stakeholders to meet business goals.

The Junior Data Engineer role involves working with data platforms, optimizing data pipelines, and collaborating with portfolio managers to meet business requirements.

Responsible for implementing AI data pipelines, developing AI-driven systems, and ensuring the reliability and scalability of data solutions while mentoring junior team members and collaborating with cross-functional teams.

The Data Engineer designs, develops, and maintains data architecture and pipelines, collaborates with teams to generate insights, and leads the implementation of analytics tools to optimize productivity.

The Data Engineer III will design, develop, and support data solutions using Azure technologies while analyzing and optimizing data processes.