4723 Data Engineer In Azure jobs in Chicago,IL

Director, Analytics, Data Engineering

Rise

Chicago, IL 60695

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field required.
Master's degree preferred.
Minimum of 10+ years of experience in data engineering, distributed systems, or enterprise data architecture.
Minimum of 5+ years designing large-scale cloud-based data platforms.
Demonstrated experience leading architectural strategy across multiple teams or business units.
Location: 4 days in office, Chicago or Sussex
This position is not eligible for visa sponsorship, including F-1 visa holders requiring CPT, OPT, or future H-1B sponsorship. Candidates must be authorized to work in the United States without current or future immigration sponsorship.
Experience in media, marketing analytics, or high-volume consumer data environments is a plus.
Knowledge of cloud-native data architectures, lakehouse and warehouse platforms, distributed computing (e.g., Spark), data orchestration frameworks, API-driven data integration, CI/CD for data platforms, and data lifecycle management and system interoperability.

SAMPRASOFT

Chicago, IL

Rise

Chicago, IL 60695

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field required.
Master's degree preferred.
Minimum of 10+ years of experience in data engineering, distributed systems, or enterprise data architecture.
Minimum of 5+ years designing large-scale cloud-based data platforms.
Demonstrated experience leading architectural strategy across multiple teams or business units.
Location: 4 days in office, Chicago or Sussex
This position is not eligible for visa sponsorship, including F-1 visa holders requiring CPT, OPT, or future H-1B sponsorship. Candidates must be authorized to work in the United States without current or future immigration sponsorship.
Experience in media, marketing analytics, or high-volume consumer data environments is a plus.
Knowledge of cloud-native data architectures, lakehouse and warehouse platforms, distributed computing (e.g., Spark), data orchestration frameworks, API-driven data integration, CI/CD for data platforms, and data lifecycle management and system interoperability.