Top Data & Analytics Jobs in Chicago, IL

Design, build, and operate big-data and streaming platforms (Kafka, Hadoop, Dremio). Develop, deploy, and monitor data pipelines using Java, Python, Spark/Flink; collaborate on data modeling and ingestion, ensure data integrity and availability, act as a Big Data SME, and perform root-cause analysis.

Lead a global analytics team to transform financial and operational data into actionable insights. Partner with stakeholders to align analytics with strategy, build scalable Power BI dashboards integrated with Snowflake, apply predictive modeling and ML, enforce data governance, drive automation with Python and Power Automate, and improve data architecture and reporting to inform decision-making and business performance.

Leads technical business analysis across engineering, product, finance, and analytics teams. Translates business and regulatory reporting needs into requirements, data models, dbt models, SQL queries, metrics, and reporting solutions. Manages projects, mentors analysts, analyzes and reconciles data, resolves quality issues, and establishes testing, documentation, auditability, and data quality standards.

Build and launch benchmark, thematic, factor, strategic beta, and multi-asset indexes from concept through market launch. Conduct quantitative research, data analysis, signal testing, back-testing, portfolio construction, risk modeling, and statistical testing. Use Python and AI tools to automate workflows and accelerate methodology development. Create prototypes, dashboards, research materials, methodology documents, and client-facing narratives while partnering with research, product, technology, operations, and commercial teams.

Lead complex data initiatives from discovery through implementation and adoption. Define data structures, integrations, governance requirements, metrics, validation criteria, and reusable patterns across heterogeneous systems. Partner with business, product, technology, and data-governance teams to establish trusted data foundations, modernize legacy processes, support platform migrations, and enable reliable operational decisions and responsible AI capabilities.

The Manager, Identity Fraud Strategy oversees identity verification and authentication strategies, leads a fraud analytics team, and partners with CIAM to minimize fraud while enhancing customer experience.

Lead the Data Platform Engineering team owning ETL/reverse-ETL pipelines, replication, and production datastores. Define architecture, roadmap, standards (IaC, observability, schema contracts), mentor engineers, drive incident response and durable fixes, and partner on cross-team technical decisions and operational reliability for data correctness, completeness, and timeliness.

Build and lead the data engineering ecosystem supporting analytics, BI, and data science. Design scalable pipelines, cloud infrastructure, Snowflake data warehouses, governance controls, validation frameworks, and machine learning workflows. Collaborate with engineering, data science, product, and business stakeholders on architecture and technology decisions. Develop AI agents and secure enterprise AI integrations, participate in on-call and incident management, document standards, and mentor data engineers.

Deployment Strategists work with customers to identify data-driven solutions, enhance operational workflows, and support decision-making by integrating and analyzing data.

Belvedere Trading seeks a Senior Data Engineer to enhance trading performance through data availability and reliability, designing ETL pipelines and data architectures in a fast-paced environment.