Top Analysis Reporting Jobs in Peoria, IL

Develop analytical solutions and actionable insights from customer, machine, technology, and utilization data. Identify adoption barriers and growth opportunities, quantify impacts on safety and productivity, define performance indicators, and collaborate with engineering, product, commercial, dealer, and field teams to build scalable analytics solutions and customer-engagement strategies.

Lead Toast’s global People Analytics function across data engineering, analytics, data science, and employee listening. Set the people data and reporting strategy, establish trusted metrics and governance, partner with executives on workforce decisions, measure People program impact with Finance, and build scalable self-service analytics. Manage a distributed US and India team, oversee executive and board-level workforce analysis, and collaborate with privacy, legal, People technology, AI, and data engineering teams.

Performs data profiling, quality analysis, governance, metadata and lineage management, and Master Data Management support. Collaborates with data owners, stewards, business stakeholders, and technical teams to resolve issues and improve governance processes. Maintains glossaries, dictionaries, controls, metrics, and reports; supports enterprise data initiatives, communications, training, and stakeholder adoption. Provides guidance to less experienced analysts while applying governance standards and documenting business requirements.

Lead enterprise data architecture across warehouses, data lakes, downstream applications, and AI workloads. Design data models, Medallion Architecture, ELT standards, semantic layers, APIs, access controls, and reusable datasets. Partner with business and BI teams to drive adoption, conduct architecture reviews, establish platform standards, and mentor data and analytics engineers. The role requires deep Snowflake, dbt, data modeling, pipeline, and semantic-layer expertise, with experience in AI data patterns and cloud infrastructure preferred.

Build Affirm’s narrative intelligence function by analyzing audience, behavioral, brand, media, survey, and business data. Develop narrative measurement frameworks, dashboards, analytical standards, and feedback loops to assess how effectively communications resonate. Design rigorous research studies, integrate qualitative and quantitative evidence, identify meaningful patterns, and translate findings into positioning, messaging, campaign, content, and communications strategy. Partner across analytics, research, marketing, creative, and communications teams to turn complex evidence into actionable decisions.

Conduct qualitative and quantitative consumer research to identify needs, trends, and product opportunities. Analyze consumer feedback, translate findings into actionable recommendations, and support product roadmaps, positioning, experience design, and go-to-market planning. Collaborate with Product Development, Marketing, and Design teams while managing research partners and multiple projects.

Leads enterprise-scale data architecture across batch, streaming, warehouse, lakehouse, transactional, AI, and vector-store use cases. Establishes data quality, governance, lineage, observability, access-control, and reliability standards. Defines AI-enabled data engineering patterns, mentors engineers, resolves complex architecture issues, and influences cross-functional roadmaps. Requires hands-on technical leadership and 15+ years of software, data engineering, or architecture experience.

Build and support enterprise data ingestion, transformation, modeling, and integration solutions using Microsoft Fabric and Azure data services. Develop batch, API, file, database, and event-driven pipelines; create dimensional and curated data models; write and optimize SQL; resolve data-quality and pipeline issues; and support production workloads. Collaborate in Agile engineering processes using GitHub, Azure DevOps, CI/CD, code reviews, and reusable development standards.

Leads data strategy for MetLife’s Group Benefits business by connecting business and Data & Analytics teams, establishing shared definitions, resolving ownership gaps, and improving governance and quality. The role leads Data Councils, supports Agile Release Trains, removes data-related blockers, and strengthens data foundations for decision-making, service delivery, analytics, and AI initiatives.

Designs and delivers large-scale, governed data pipelines and infrastructure across the full data lifecycle. Responsibilities include coding in Python and SQL, optimizing Airflow, dbt, AWS, Kafka, and Iceberg/Parquet workflows, implementing data quality and observability, contributing to architecture and tool evaluations, mentoring engineers, collaborating with stakeholders, and participating in on-call support.