Top Data & Analytics Jobs in Peoria, IL

Build and optimize Customer 360 data models, ELT pipelines, semantic layers, and identity resolution frameworks in BigQuery. Develop Tableau dashboards for customer acquisition, retention, churn, product adoption, and deposits. Sync behavioral data with marketing and CRM platforms such as Braze, implement data quality and observability controls, and partner with Marketing, Product, and business leaders to turn customer analytics into growth initiatives.

Leads the architecture, development, and production operation of complex data pipelines and platforms. Resolves scalability, data quality, reliability, and architectural challenges; evaluates data technologies; mentors engineers; establishes engineering standards; partners with product, analytics, and operations teams; communicates technical trade-offs; and conducts proofs of concept to guide platform strategy.

Leads consumer, category, market, and growth insights across infant formula and new ventures. Supports qualitative and quantitative research, opportunity sizing, commercialization, pricing, go-to-market strategy, KPI dashboards, syndicated data analysis, campaign evaluation, launch measurement, and executive reporting. Partners cross-functionally with Innovation, Marketing, Sales, Product Development, Finance, research agencies, and data providers to translate intelligence into actionable growth recommendations.

Design and maintain scalable dbt data models and ELT pipelines in Snowflake; architect reusable data assets, governance, and SaaS metrics; build AI-enabled data foundations and LLM workflows; integrate analytics into operational tools and partner cross-functionally to productionize AI-driven use cases.

Design and maintain scalable dbt data models and ELT pipelines in Snowflake. Architect data foundations to power AI and LLM-enabled workflows, operationalize core SaaS metrics, and build reusable data assets for analytics and activation. Partner cross-functionally to embed analytics into workflows and ensure scalable, secure architecture.

Build and scale secure data lakehouse and warehouse infrastructure supporting analytics, machine learning, clinical AI performance monitoring, and self-service insights. Develop scalable data pipelines, models, orchestration, quality controls, and LLM-enabled analytics tools using heterogeneous clinical and EHR data. Collaborate with engineering, data science, clinical, product, and client success teams to establish trustworthy metrics and technical solutions.

Design and maintain enterprise semantic models, ontologies, taxonomies, and knowledge graphs. Define business concepts and metadata standards, map technical data to shared definitions, and partner with data architecture, engineering, governance, AI, and business teams to enable discovery, analytics, and AI-ready semantic solutions.

Develop and maintain Power BI dashboards, reports, KPIs, and business systems supporting commissioning, quality, and infrastructure projects. Gather requirements, improve workflows and data quality, coordinate user acceptance testing, manage enhancement requests, and validate reporting accuracy. Collaborate with operational, engineering, construction quality, and regional stakeholders to support governance, project readiness, issue tracking, and data-driven decision-making. Create documentation, training materials, and communications for system releases and reporting changes.

Designs, develops, and supports supply chain reporting, analytics, and AI-assisted workflow solutions. Responsibilities include building Power BI dashboards, Snowflake data and semantic models, DAX measures, Power Query transformations, KPI visualizations, workflow solutions, data validation, technical documentation, deployment support, and stakeholder engagement across procurement, inventory, warehousing, logistics, and supplier processes.

Build and maintain data pipelines, SQL queries, data models, database structures, and centralized data warehouse capabilities. Clean and validate data, develop reporting datasets and solutions, support KPI tracking and historical analysis, and collaborate with Finance and Revenue Operations. Investigate data gaps, troubleshoot integrations, and independently deliver reliable technical solutions.