Top Data & Analytics Jobs in Chicago, IL

Design, build, and operate scalable cloud data platforms, pipelines, and applications. Collaborate with Agile teams, product managers, software engineers, analysts, and data scientists to deliver secure, resilient data solutions. Apply Python, Spark, SQL, relational and NoSQL databases, Databricks, Snowflake, and cloud technologies. Establish engineering patterns, data security controls, observability, and operational best practices while mentoring team members and communicating technical outcomes to stakeholders.

Manage data governance and risk programs for Global Payment Networks. Analyze large datasets, build and validate models, improve data and reporting processes, establish controls, support privacy and regulatory compliance, and lead cross-functional projects. The role also includes mentoring junior analysts, managing concurrent initiatives, and consulting on data systems, product testing, and business intelligence solutions.

Design, build, and operate scalable cloud data platforms, pipelines, and applications. Lead architectural decisions, establish reusable engineering patterns, evaluate technologies such as Snowflake and Databricks, and deliver distributed, real-time, and warehouse solutions. Collaborate with product, engineering, analytics, and data science teams while mentoring engineers and communicating technical outcomes to stakeholders.

Design, build, and support scalable cloud data platforms, pipelines, and applications. The role involves distributed data processing, data modeling, relational and NoSQL databases, data security, observability, orchestration, and real-time pipelines. It also requires influencing cross-functional teams, mentoring data professionals, establishing engineering standards, and communicating technical outcomes to stakeholders.

Design, build, and support scalable cloud data platforms, pipelines, and applications. Collaborate with Agile teams, product managers, engineers, analysts, and data scientists to deliver data solutions. Develop distributed and real-time workloads, enforce reusable engineering patterns, apply security controls, and optimize reliability and performance. Mentor data professionals, communicate technical concepts to stakeholders, and independently architect end-to-end solutions using relational and NoSQL databases, cloud warehouses, and modern data engineering technologies.

Leads data engineering teams and technical strategy for scalable cloud data platforms. Oversees architecture, pipelines, data models, quality, observability, and operational standards across Databricks, Spark, Python, and Snowflake environments. Mentors engineers, drives large-scale data initiatives, evaluates platform choices, and collaborates with product and software teams to deliver reliable data solutions.

Designs, builds, and operates scalable cloud data platforms, pipelines, and applications using Python, SQL, Spark, AWS, Databricks, Snowflake, and distributed data technologies. The role includes data modeling, real-time processing, data security, observability, architecture standards, stakeholder communication, mentoring, and collaboration with product, engineering, analytics, and machine learning teams.

Leads data analysis and AI-readiness initiatives for the personal loans business, including data governance, quality, automation, reporting, and analytics. Manages complex data analysis projects, improves processes and customer experiences, evaluates products and marketing initiatives, and collaborates across business units. Mentors junior analysts and contributes to data system design, business intelligence, and strategic testing.

Leads data analytics and AI-readiness initiatives for the personal loans business. Responsibilities include improving data governance and quality, automating monitoring controls, building data abstraction layers, analyzing large databases, evaluating products and processes, enhancing business intelligence, and mentoring junior analysts. The role involves cross-functional collaboration, strategic testing, reporting improvements, and consulting on data systems while managing concurrent projects.

Designs, builds, and operates scalable cloud data pipelines, platforms, and applications. Responsibilities include distributed data processing, data modeling, relational and NoSQL database development, data security, observability, orchestration, and data warehousing. The role collaborates with engineering, analytics, product, and data science teams; establishes reusable engineering patterns; communicates technical concepts; and mentors data professionals.