Top Tech Jobs & Startup Jobs in Chicago, IL

Leads web analytics strategy, GA4 and GTM implementations, tagging specifications, dashboards, reporting, experimentation, and data-quality monitoring. Analyzes user behavior, conversion funnels, feature adoption, and A/B test results to provide actionable recommendations for product and business decisions. Partners with product, engineering, UX, and business stakeholders and communicates analytical findings to technical and non-technical audiences.

Analyze business processes, data quality, and datasets to identify AI and automation opportunities. Translate business requirements into AI/ML use cases, collaborate on model development, evaluate model performance, and deliver dashboards and reports. The role also supports data validation, AI solution monitoring, emerging technology research, governance, compliance, responsible AI, prompt engineering, and generative AI initiatives while partnering with business, data science, engineering, and product teams.

Lead development of an enterprise Agentic AI platform, cloud deployment frameworks, and autonomous workflows. Manage 35+ engineers and multiple technical leaders while overseeing architecture, delivery, hiring, budgets, customer implementations, cloud modernization, observability, security, compliance, AI governance, and technical proofs of concept. Collaborate with product, business, executive, and customer teams to align requirements and engineering outcomes across AWS, Azure, and Google Cloud.

Lead technical programs for branded card products, including launches, enhancements, and digital wallet integrations. Manage roadmaps, timelines, budgets, risks, dependencies, and stakeholder communication across engineering, QA, product, risk, compliance, and design teams. Track milestones using Jira dashboards, resolve cross-functional issues, report progress, and improve delivery processes. The role requires strong software development knowledge, Agile experience, database querying skills, cloud familiarity, and understanding of microservices architecture.

Analyzes business processes, data quality, and datasets to identify AI and automation opportunities. Translates business requirements into AI/ML use cases, collaborates on model development, evaluates model performance, and creates dashboards and reports. The role monitors AI solutions, researches emerging technologies, and supports governance, compliance, responsible AI, and prompt engineering initiatives while partnering with data scientists, engineers, product teams, and business stakeholders.

Develop and maintain scalable Snowflake data warehouses, ETL/ELT pipelines, data models, and integrations across cloud and on-premises sources. Optimize queries, clustering, partitioning, and warehouse performance; implement transformations using SQL, stored procedures, and Snowpark. Monitor data quality, governance, security, deployments, and production issues. Collaborate with engineers, architects, analysts, and business stakeholders while automating workflows and contributing to data architecture and best practices.

Design, develop, and maintain automated testing solutions for customer-facing applications and web services. Build test frameworks, integrate tests into CI/CD pipelines, and improve coverage, reliability, security, and release quality. Develop front-end and web-service automation using Groovy/Geb and Java/HttpClient, troubleshoot application issues, participate in code and test reviews, and collaborate with Agile development teams throughout the software lifecycle.

Develop and maintain responsive web applications using Angular, JavaScript, and TypeScript. Build reusable UI components, integrate REST APIs, translate designs into functional interfaces, and optimize performance, accessibility, and browser compatibility. Troubleshoot issues, participate in testing and code reviews, and collaborate with designers, backend developers, QA, and product teams in an Agile/Scrum environment.

Build and maintain scalable full-stack web applications across front-end and back-end systems. Develop RESTful APIs, integrate AI and machine-learning models using Python, manage SQL and NoSQL databases, and create GitHub Actions CI/CD pipelines. Collaborate with data scientists, troubleshoot and improve existing software, participate in code reviews, and apply modern DevOps, cloud, containerization, and microservices practices.

Lead the planning, execution, monitoring, and delivery of enterprise technology projects. Manage scope, timelines, budgets, resources, risks, vendors, and stakeholder communications while coordinating cross-functional teams across Agile, Scrum, and Waterfall environments. Projects may include software development, cloud transformation, application modernization, and enterprise technology implementations. Ensure business and technology objectives are achieved across multiple concurrent initiatives.