Top Data & Analytics Jobs in Chicago, IL

Manage data analytics for PULSE Risk & Compliance by analyzing large datasets, identifying transaction anomalies and risk exposure, validating models, improving reporting and processes, and supporting compliant data strategies. The role involves Python-based programming, BI, database and data-storage design, strategic testing, cross-functional collaboration, project leadership, and people management in a hybrid environment.

Leads enterprise-wide validation of analytical tools, including planning validation projects, assessing methodology quality and tool risk, researching best practices, and communicating findings through reports and presentations. Partners cross-functionally to influence business strategy, handles concurrent projects, develops solutions to business problems, and coaches junior staff. The role requires substantial data analysis, statistical or econometric modeling, large-scale data manipulation, open-source technology experience, and people management.

Designs, builds, and operates scalable cloud data pipelines, platforms, and applications. Responsibilities include data modeling, distributed data processing, relational and NoSQL database development, architecture decisions, observability, streaming pipelines, and data warehousing. The role leads large-scale data initiatives, evaluates technologies such as Snowflake and Databricks, collaborates with product and engineering teams, communicates technical concepts, and mentors data engineers.

Design, build, and operate scalable cloud data platforms, pipelines, and applications using distributed data technologies. Lead architectural decisions, data modeling, platform selection, and large-scale transformation initiatives. Collaborate with product managers, software engineers, analysts, and data scientists while ensuring resilience, maintainability, and operational efficiency. Mentor engineers, establish engineering standards, communicate technical outcomes, and independently deliver end-to-end data solutions across relational, NoSQL, batch, and streaming environments.

Design, build, and architect scalable cloud data platforms, pipelines, and applications. Lead large-scale data initiatives, make architectural decisions, evaluate technologies such as Snowflake and Databricks, enforce engineering patterns, and ensure performance and resilience. Collaborate with product, engineering, analytics, and data science teams while mentoring engineers and communicating technical outcomes to stakeholders.

Lead data analytics strategy, mine and analyze large-scale datasets, build and validate models, improve reporting and operational processes, evaluate products and marketing initiatives, and consult on data systems. Manage and mentor junior analysts, collaborate across business units, oversee concurrent projects, and apply business intelligence tools to support customer experience and organizational decision-making.

Build and architect scalable cloud data platforms, pipelines, and applications using Python, Spark, SQL, Databricks, Snowflake, and relational and NoSQL databases. Collaborate with engineering, product, analytics, and data science teams; implement secure and resilient data solutions; enforce reusable engineering patterns; communicate technical outcomes; mentor colleagues; and support distributed, real-time, and cloud-based workloads.

Analyze complex data, develop self-service data solutions, build business intelligence tools and dashboards, deliver strategic insights, and manage data quality, metadata, lineage, security, and access governance. The role requires scripting, querying, visualization, Snowflake development, and collaboration with business and technology teams.

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.