Top Senior Data & Analytics Jobs in Chicago, IL

Leads data engineering teams and develops cloud-based, distributed, and full-stack data solutions. Responsibilities include designing, coding, testing, reviewing, and supporting systems using big data technologies, cloud data warehouses, streaming applications, machine learning systems, microservices, and NoSQL databases. The role also involves mentoring engineers, collaborating with product managers and Agile teams, optimizing performance, and driving technology transformation.

Analyze complex data and develop managed data solutions, business intelligence tools, dashboards, metrics, and self-service capabilities. Partner with business and technology teams to deliver strategic insights, manage data quality, metadata, lineage, security, and access governance. The role requires scripting, querying, visualization, Snowflake development, and familiarity with cloud services and data governance.

Analyzes AML and KYC data, builds regulatory reporting dashboards, develops KPIs and KRIs, identifies compliance risks and trends, improves processes and reporting, and advises leadership and business units. The role manages complex datasets, supports AML program health analysis, collaborates across teams, and contributes to projects involving data quality, operational efficiency, and compliance risk management.

Lead the architecture and delivery of Salesforce Marketing Cloud and Data Cloud solutions for partner marketing. Design data models, knowledge graphs, identity resolution, batch and streaming pipelines, APIs, zero-copy integrations, and AI-enabled workflows. Establish orchestration, monitoring, CI/CD, governance, and reliability standards while mentoring engineers and partnering with marketing, data science, and Salesforce stakeholders.

Leads sales and business intelligence analytics, including pipeline ROI, incentive analysis, forecasting, year-over-year drivers, and connectivity trends. Develops dashboards, analytical tools, methodologies, and business processes using internal and external data. Partners with cross-functional stakeholders and IT to define requirements, integrate systems, and communicate actionable insights to leadership. Requires strong quantitative analysis, data visualization, stakeholder communication, and project leadership skills.

Lead consumer lending analytics and strategy across credit card, HELOC, and Auto/RV products. Evaluate portfolio performance, member behavior, pricing, targeting, risk, profitability, and growth opportunities. Develop strategic recommendations, forecasts, business cases, and analytical frameworks using SQL and large datasets. Partner with finance, credit risk, marketing, operations, and technology leaders while managing, coaching, and developing an analytics team.

Lead e-commerce fulfillment analytics and strategic planning across five grocery brands. Build models and market outlooks, generate actionable insights, present recommendations to executives, partner cross-functionally to optimize capacity, sales capture, and costs, and drive continuous improvement of processes and team capabilities.

Leads technical delivery of Master Data Management solutions using Informatica MDM and PowerCenter. Designs and implements ETL mappings, workflows, transformations, data quality processes, governance practices, SQL data marts, and Python automation. Oversees MDM specialists, monitors production jobs, troubleshoots operational issues, supports testing and validation, tunes performance, documents technical solutions, and collaborates with state agencies, QA, business teams, and project leadership.

Provides analytics-driven strategic advice for mergers, acquisitions, and other transactions. Responsibilities include analyzing contract data, developing algorithms and predictive models, integrating data sources, building pipelines, creating dashboards, validating data integrity and security, and identifying risks and compliance indicators. The role also involves client collaboration, mentoring junior staff, and delivering data-driven insights using Python and machine learning.

Owns the full lifecycle of business intelligence solutions, including requirements gathering, dashboard and report development, data modeling, visualization, governance, and production delivery. Partners with business, laboratory, engineering, and product stakeholders to perform root-cause analyses, develop datasets, support self-service analytics, and guide system changes. Requires advanced SQL, BI tool expertise, stakeholder management, and experience with agentic workflows.

Lead advanced risk, fraud, and payment optimization analyses for major fintech merchants. Analyze large-scale transactional, ML output, and labeled risk data; design experiments and statistical investigations; develop scalable analytical tools, ETL workflows, dashboards, and reusable frameworks; collaborate with risk product teams; translate findings into merchant strategies and product improvements; enable commercial stakeholders through playbooks and self-service tools; and mentor analysts.

Designs and maintains enterprise BI reporting, analytics applications, data marts, warehouses, and ETL/ELT pipelines. Partners with cross-functional stakeholders to gather requirements and deliver scalable solutions using SQL, Python, Snowflake, Airflow, and BI visualization tools. Leads initiatives through architecture, implementation, delivery, and support, while advancing AI adoption across the BI and data development workflow.