Top Senior Data & Analytics Jobs in Chicago, IL

Leads data engineering and analytics engineering teams delivering production pipelines, curated data products, semantic models, dashboards, and governed Databricks lakehouse capabilities. Owns platform administration, data quality, observability, security, cost optimization, reliability, and engineering standards. Manages internal and external resources, mentors engineers, drives AI-assisted development, partners with stakeholders, and reports roadmap progress to leadership. Requires strong hands-on Databricks expertise, technical leadership, advanced SQL, data modeling, CI/CD, and up to 5% travel.

Leads the Data Engineering team and sets technical direction for the company’s data platform. Owns Snowflake, PostgreSQL, pipelines, modern ELT tooling, Medallion architecture, reliability, scalability, cost optimization, data quality, observability, governance, and security. Partners across Engineering, Analytics, Product, Finance, Risk, and Marketing to deliver reusable data solutions. Develops engineers, establishes standards, communicates technical tradeoffs, and builds a long-term platform roadmap supporting analytics, automation, and AI.

Develop and improve IP geolocation automation algorithms using large datasets and IP network topology. Query, extract, and transform data with SQL, R, Python, MongoDB, and BigQuery; provide insights that improve data quality; and collaborate with engineers, data scientists, and stakeholders to solve complex problems and lead data science initiatives.

Analyzes large, complex datasets from multiple sources to support Inspector General investigations. Responsibilities include data extraction, quality validation, discrepancy resolution, statistical and narrative reporting, dashboard and BI solution development, SQL querying, application and script modification, process documentation, and presenting findings. The role requires substantial data analysis and management experience, programming knowledge, and familiarity with visualization, database, statistical, and reporting tools.

Designs, builds, and maintains secure data pipelines, ETL processes, data warehouses, and quality controls. Collects, validates, cleanses, and analyzes data; develops SQL queries, Tableau dashboards, and AWS-based solutions; investigates data integrity issues; documents standards; and partners with stakeholders to deliver technical solutions using Agile and DevOps practices.

Leads a team of data analysts while delivering business intelligence insights across Marketing, Product, Operations, and Finance. Owns the Tableau environment, including governance, permissions, licensing, data quality, and platform capabilities. Develops dashboards, KPI frameworks, and analytics roadmaps; oversees marketing attribution and campaign measurement; partners with Data Engineering on data availability; and drives stakeholder adoption of analytics products.

Designs and manages advanced data architectures, pipelines, ingestion frameworks, and data quality processes. Develops scalable data solutions across cloud, warehouse, lakehouse, and distributed computing platforms. Builds data consumption methods such as APIs, database views, and extracts while managing lineage, privacy, compliance, and transformation rules. Collaborates cross-functionally to improve data sourcing, accessibility, reliability, and processing efficiency.

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.

Build and operate scalable healthcare data pipelines, dbt models, event-driven services, APIs, and Google Cloud infrastructure. Model and govern multimodal EHR, genomic, and imaging data for AI agents across federated hospital networks. Ensure data quality, lineage, observability, security, HIPAA compliance, and production reliability while contributing to TypeScript application services and agentic workflows.

Architect and own NinjaTrader’s foundational dbt data-model layer, establish modeling standards, and manage paid-media attribution. Develop AI-driven reporting, data-quality automation, agentic workflows, and self-service knowledge tools. Partner with Data and MarTech teams, prevent pipeline issues, scale models across business units and geographies, and mentor teammates while applying marketing measurement concepts such as CAC, LTV, and ROAS.