Top Data & Analytics Jobs in Peoria, IL

Build and maintain scalable batch and incremental data pipelines using Python, SQL, and Snowflake. Develop data warehouse models, transformations, automation, quality checks, lineage, alerting, and performance optimizations. Collaborate with analysts, data scientists, and application teams to deliver trusted datasets, while documenting pipelines, schemas, and data contracts.

Leads the design, delivery, and optimization of data architecture, pipelines, semantic layers, data quality frameworks, and Tableau BI platforms. Partners with stakeholders to manage requirements, project plans, sprint execution, monitoring, governance, and release delivery. Guides data engineers, manages team members, and supports AI-enabled analytics capabilities. Requires strong SQL, Spark, PySpark, SSIS, cloud data platform, CI/CD, Tableau infrastructure, and data engineering expertise.

Designs and maintains a scalable data platform supporting analytics, machine learning, and AI workloads. Builds tooling for reliable data pipelines, semantic layers, data agents, LLM applications, and evaluation systems. Ensures data quality, availability, observability, and reliability while establishing modeling, testing, and platform best practices. Collaborates with Data Science and Product Engineering, leads solutions from design through implementation, and contributes individually in a fast-paced startup environment.

Lead the enterprise data governance program, roadmap, operating model, policies, standards, governance bodies, and owner/steward accountability. Build data domains, taxonomies, contracts, lineage, metadata, and audit controls across complex multi-brand platforms. Partner with Technology, Legal, Privacy, Security, Risk, Compliance, and business leaders to ensure trustworthy data for analytics and AI. Manage governance leads and communicate strategy, risks, and recommendations to senior executives and auditors.

Own the technical design and operation of Palmetto’s governed data platform. Build trusted data products, semantic models, ingestion and transformation pipelines, secure access interfaces, and agent-ready data services. Establish governance, masking, authorization, observability, CI/CD, and audit readiness. Partner with finance, operations, product, and engineering teams while mentoring engineers and setting cross-team technical direction.

Build executive-facing dashboards, scalable data models, semantic layers, and reporting datasets using dbt, Looker, and SQL. Analyze large datasets, identify trends and anomalies, manage the Looker analytics platform, resolve data quality issues, and deliver analytics initiatives across business domains. Partner with product, engineering, finance, and operations stakeholders to define metrics and reporting solutions. Mentor junior analytics engineers and improve analytics standards and documentation.

Complete and document real-world Google Analytics workflows involving reports, traffic, users, events, conversions, audience insights, and engagement metrics. Record screen demonstrations, create prompts and rubrics, explain workflow steps, review outputs for accuracy, and follow project quality standards independently in a remote contract environment.

Build, test, and maintain batch and event-driven data pipelines and ETL/ELT workflows. Transform and validate large datasets, troubleshoot data-quality issues, improve workflow reliability, and support platform modernization. Collaborate with engineering, product, and data stakeholders while following strong practices for version control, testing, monitoring, documentation, and code review. The role may occasionally require work outside standard business hours.

Design and implement attribution, source tracking, CRM integrations, ROI measurement, funnel reporting, and sales performance systems for B2B clients. Consult with revenue leaders, define metrics, build and validate reporting across marketing, sales, CRM, advertising, and BI platforms, troubleshoot data quality issues, document solutions, and train client teams. Contribute to implementation methodologies, technical content, automation, and AI-enabled data validation and analysis.

Lead analytics and data science initiatives to drive measurable business outcomes across various functions, including Underwriting and Claims. Oversee the full analytics lifecycle, foster stakeholder engagement, and mentor junior team members.