6454 Data Engineer Data Ops jobs in Chicago,IL

Data Science Manager - Space Intelligence (Remote)

The Home Depot

Chicago, IL

WORLDPAC

Oak Brook, IL 60523

Bachelor's degree in Data Science, Statistics, Mathematics, Business Analytics, Information Technology, Business Administration, or a related field.
5 - 7 years of experience as a Data Analyst, BI Analyst, or similar analytics-focused role.
Strong SQL skills with hands-on experience querying cloud data warehouses (Snowflake strongly preferred).
Demonstrated advanced/expert level experience building dashboards and reports using Power BI, including use of semantic models and Microsoft Fabric.
Experience defining and validating KPIs and business metrics.
Solid understanding of descriptive and basic inferential statistics for business analysis.
Advanced Excel for analysis and modeling.
Understanding data governance, metric standardization, and data quality concepts.
Experience working in agile analytics or BI environments using Jira and Confluence, ServiceNow and/or similar tools.
Strong analytical thinking, attention to detail, and problem-solving skills.
Excellent written and verbal communication skills, with the ability to convey insights clearly to non-technical audiences.

Scalepex

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.