Top Data & Analytics Jobs in Chicago, IL

Leads data engineering and analytics engineering teams delivering production pipelines, curated data products, semantic models, dashboards, and governed Databricks lakehouse capabilities. Owns platform administration, data quality, observability, security, cost optimization, reliability, and engineering standards. Manages internal and external resources, mentors engineers, drives AI-assisted development, partners with stakeholders, and reports roadmap progress to leadership. Requires strong hands-on Databricks expertise, technical leadership, advanced SQL, data modeling, CI/CD, and up to 5% travel.

Own marketing funnel analytics from end to end by monitoring metrics, diagnosing performance drivers with SQL and Python, building Snowflake/dbt models, and maintaining Periscope dashboards. Translate findings into actionable recommendations for leadership, partner with Marketing, Risk, and Engineering on strategy and release impact analysis, and use AI tools while validating their output. Support team development through knowledge sharing, code review, and mentoring junior analysts.

Develop accurate, scalable data visualizations, dashboards, data models, and documentation using clinical and enriched healthcare data. Perform custom analyses for account managers and clinical partners, support data investigations, and collaborate with product, engineering, clinical, and account teams. Ensure data product quality and timeliness while building solutions with SQL, relational data, Looker, and business intelligence tools.

Develop and improve IP geolocation automation algorithms using large datasets and IP network topology. Query, extract, and transform data with SQL, R, Python, MongoDB, and BigQuery; provide insights that improve data quality; and collaborate with engineers, data scientists, and stakeholders to solve complex problems and lead data science initiatives.

Analyzes large, complex datasets from multiple sources to support Inspector General investigations. Responsibilities include data extraction, quality validation, discrepancy resolution, statistical and narrative reporting, dashboard and BI solution development, SQL querying, application and script modification, process documentation, and presenting findings. The role requires substantial data analysis and management experience, programming knowledge, and familiarity with visualization, database, statistical, and reporting tools.

Designs, builds, and maintains secure data pipelines, ETL processes, data warehouses, and quality controls. Collects, validates, cleanses, and analyzes data; develops SQL queries, Tableau dashboards, and AWS-based solutions; investigates data integrity issues; documents standards; and partners with stakeholders to deliver technical solutions using Agile and DevOps practices.

Analyzes customer segments, KPIs, trends, and data quality to identify insights supporting acquisition, engagement, retention, and revenue growth. Partners with stakeholders on ad hoc analyses, develops dashboards and recurring reports, creates presentation materials, and translates findings into data-driven recommendations. The role requires customer data analysis, reporting, data visualization, and cross-functional collaboration in an e-commerce environment.

Leads revenue growth analytics across pricing, promotions, assortment, and market trends. Develops pricing models, promotional strategies, forecasts, KPIs, dashboards, and predictive analyses to improve sales and profitability. Partners with Sales, Marketing, Finance, and Category Management to provide actionable recommendations, influence strategic decisions, and support planning across retail, commercial, eCommerce, and direct-to-consumer channels.

Leads a team of data analysts while delivering business intelligence insights across Marketing, Product, Operations, and Finance. Owns the Tableau environment, including governance, permissions, licensing, data quality, and platform capabilities. Develops dashboards, KPI frameworks, and analytics roadmaps; oversees marketing attribution and campaign measurement; partners with Data Engineering on data availability; and drives stakeholder adoption of analytics products.

Leads enterprise data warehouse, reporting, analytics, and transaction-processing architecture and modernization. Designs scalable on-premises and cloud solutions, modernizes ETL and SQL into Python automation, oversees BI delivery, and establishes DevOps and CI/CD practices. Provides hands-on technical leadership across development, testing, deployment, performance, security, and support. Leads proof-of-concepts, produces architecture documentation, presents recommendations, and mentors architects, engineers, developers, analysts, and testers.