Top Data & Analytics Jobs in Peoria, IL

Leads healthcare quality analytics using hospital performance, national rankings, Medicare claims, and CMS data. Replicates quality methodologies, identifies improvement opportunities, builds dashboards and benchmarking tools, and establishes analytic validation standards. Presents insights to executives and customers, supports pre-sales and engagements, partners with data scientists and consultants, and mentors analysts.

Designs, develops, tests, and executes SQL-based data migrations and integrations for higher education Advancement systems. Builds data pipelines, staging tables, transformation logic, stored procedures, validation processes, and database-driven integrations connecting legacy platforms, institutional databases, and Salesforce. Configures Salesforce, troubleshoots data and performance issues, supports migration testing and deployments, and collaborates with architects, consultants, and client stakeholders. Periodic travel and client relationship development are required.

The Analytics Manager analyzes complex datasets, builds models, conducts scenario analyses, and provides strategic recommendations to guide decision-making for leadership.

Analyze marketing performance and ROI across markets, identify expansion opportunities, evaluate market saturation and competition, and support investment decisions. The role requires advanced SQL, funnel analysis, dashboard development, multi-source data integration, statistical reasoning, and clear communication of recommendations to marketing and leadership. The analyst will also use AI tools such as Claude and partner with data engineering to improve data quality and decision support.

Reviews and compares AI chatbot responses using predefined criteria for accuracy, relevance, completeness, clarity, consistency, and quality. Documents evaluation guidelines, analyzes workflows and data, identifies recurring issues, prepares reports, tracks quality metrics, and collaborates with project teams. This fully remote, 16-week contract requires 8 hours per day, five days per week, with Pacific Time overlap and possible weekend work.

Leads the architecture and evolution of scalable data platforms, pipelines, and data products across multiple teams. Designs Snowflake and cloud-based solutions for batch, streaming, CDC, ingestion, transformation, orchestration, and data delivery. Establishes engineering standards, governance, observability, testing, CI/CD, and reliability practices; mentors engineers; guides architecture and roadmap decisions; resolves complex incidents; and evaluates AI, automation, and MCP-enabled data capabilities.

Design and build cloud-agnostic Databricks Lakehouse architectures, scalable ETL/ELT pipelines, and production AI data workflows. Optimize Apache Spark performance, integrate MLflow for model deployment, and implement CI/CD and Infrastructure-as-Code using Terraform or Databricks CLI. Enforce governance, security, and compliance standards through Unity Catalog and cloud platforms. Collaborate with architects, scientists, product managers, and client engineering teams to deliver documented, production-ready solutions.

Own analytics as an internal data product across GTM, People, Finance, and related functions. Translate ambiguous business questions into self-service data solutions, deliver executive-ready narratives, manage stakeholder priorities, and guide data-driven decisions. Serve as a marketing analytics subject matter expert across attribution, campaign measurement, lead tracking, funnel analysis, predictive modeling, and experimentation. Use SQL, modern data-stack tools, BI platforms, and AI-assisted modeling to deliver actionable insights.

Build and operate data-intensive web products and APIs, extend high-throughput ETL pipelines and scrapers, ensure reliability/observability, design self-scaling services, participate in code review, and collaborate across product, data, and infrastructure teams to meet production SLAs.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.