Top Data & Analytics Jobs in Chicago, IL

Lead and mentor a data engineering team to design, build, test, and support cloud-based data solutions. Develop distributed, real-time and batch data pipelines using Java/Scala/Python, NoSQL and RDBMS, and cloud data warehousing (Redshift/Snowflake). Collaborate with product managers and Agile teams to deliver performant, production-ready systems.

Lead Data Engineer responsible for designing, developing, testing, implementing, and supporting cloud-based data solutions. Collaborate across Agile teams to build distributed, real-time data and streaming systems, mentor engineers, perform unit tests and code reviews, and leverage big data, NoSQL, and cloud data warehousing technologies.

Lead and mentor engineering teams to design, build, test, and support cloud-based data solutions. Work with big data, streaming, and data warehousing technologies, collaborate with product managers, and ensure performant, well-tested code and architectures.

Lead and mentor a team of data engineers to design, develop, test, implement, and support cloud-based data platforms and full-stack solutions. Build distributed, real-time, and batch data systems using Java/Scala/Python, big data tools (Spark, Hadoop, Kafka), NoSQL and RDBMS, and data warehouses (Redshift, Snowflake). Collaborate with Agile teams, perform unit tests and code reviews, and drive technology experimentation and transformation.

Design and build scalable data solutions for high-volume transaction streams. Partner with product and business teams to deliver analytics, dashboards, and insights. Lead data strategy, architecture, governance, quality, lineage, and access controls. Enable self-service capabilities and explore new open-source technologies to support business intelligence and operational needs.

Lead a team to analyze large-scale datasets, build and validate models, improve reporting and operational efficiency, design data/storage systems, run strategic tests, and collaborate across business units to drive analytics strategy and customer experience.

Lead validation of enterprise analytical tools: refine validation framework, plan and execute projects, assess methodology quality and risk, prototype best practices, communicate findings, and coach junior staff.

Lead a team delivering enterprise-wide model risk reporting and AI-driven automation. Build and deploy scalable ML/AI solutions, conversational reporting, multi-agent workflows, and centralized data integrations. Drive analytics strategy, validate models and data, improve reporting and operational efficiency, and collaborate across business units.

Lead design, build, test, and support large-scale data pipelines and cloud-based solutions. Collaborate with Agile teams, mentor engineers, optimize performance, and work with ML, streaming, and data warehouse technologies to drive customer acquisition and analytics at scale.