Analytics Engineer jobs in Chicago, IL

Build and maintain data pipelines and standardized, well-modeled datasets from billing, claims, denial, and payment systems to support reliable revenue cycle reporting. Develop analytics and self-service reporting tools, implement data quality and governance practices, and collaborate with analysts and stakeholders to investigate discrepancies and identify trends.

The Senior Data and Analytics Engineer will design, develop, and deploy scalable data pipelines and analytics solutions to support supply chain operations. They will provide technical leadership, ensure data quality and security, and collaborate with cross-functional teams to deliver AI-ready data products.

Lead data-driven initiatives and develop innovative analytics solutions to optimize business performance and provide strategic insights. Manage client service accounts, supervise teams, and ensure the successful execution of complex projects while upholding professional standards.

The Analytics and Insights Engineer III designs and executes analyses to address client business questions across paid, owned, and earned channels. They are responsible for developing measurement frameworks, performance reporting, and deploying experimentation strategies using various data tools.

You will architect and own the marketing data infrastructure, including ETL/ELT pipelines and Databricks models to power self-serve analytics and AI agents. Additionally, you will partner with cross-functional teams to define the technical roadmap and translate ambiguous business questions into scalable data products.

Lead the design, development, and optimization of complex Tableau dashboards while providing technical direction across a large analytics portfolio. Mentor developers, drive AI-assisted engineering practices, and partner with senior leadership to advance operational efficiency and data strategy.

You will design, develop, and maintain robust data models and semantic layers to serve as a single source of truth for the Mars Accelerator division. Additionally, you will collaborate with cross-functional teams to build high-impact KPI dashboards and integrate predictive intelligence into analytical workflows.

Develop, maintain, and optimize scalable data pipelines, models, datasets, and reporting solutions using technologies such as dbt, SQL, and Power BI. Support migrations, testing, deployment, maintenance, and performance troubleshooting while collaborating with stakeholders and providing technical guidance to junior team members.

The role involves owning the end-to-end delivery of healthcare analytics products and contributing to the development of the Insights Agent (IAA) platform. You will collaborate with clinical consultants to translate domain requirements into software while managing data pipelines and application deployments.

Engage with Corporate Services and HR stakeholders to understand business processes and translate their needs into scalable data and automation solutions that deliver measurable efficiency gains. Architect, prototype, implement, and maintain production-ready solutions, while mentoring technical staff and collaborating across teams to accelerate value.

Design and implement modern lakehouse architectures using Microsoft Fabric and Databricks while building performant ELT/ETL pipelines. Act as a trusted technical advisor to enterprise clients by delivering complex Power BI reports and scalable semantic models.

Provide senior technical leadership for Analytics Engineering, shaping data foundations, modeling standards, architecture, governance, quality, tooling, and developer experience. Build trusted canonical datasets, semantic layers, and AI-enabled analytical tools that support self-service analytics and improve decision-making across the company.

Own canonical data models and KPI definitions for payments, billing, subscriptions, identity, and Trust & Safety across Scribd, Everand, and Fable. Improve data quality, observability, and lineage; build AI tools on certified data; and set technical standards while influencing partners and mentoring colleagues.

Support nationwide deployment of a case management platform used for docketing, scheduling, case tracking, and caseload reporting. Train legal and administrative users, provide deployment support, troubleshoot issues, and develop documentation and knowledge resources.

The Analytics Platform Engineer will design, build, and operate Huron's enterprise cloud data platform using AWS and Python. Responsibilities include developing scalable data pipelines, automating platform services, and improving developer experience for analytics teams.

Lead the development of healthcare analytics products by designing ETL processes, managing data pipelines, and implementing machine learning algorithms. Collaborate with cross-functional teams to drive innovation and optimize development workflows to improve patient outcomes.

The Analytics Engineer will own the analytics engineering process, building and optimizing data pipelines and architecture to transform raw data into reliable, analytics-ready models. They will partner with cross-functional teams to define KPIs, implement data quality standards, and ensure scalable data delivery.

The Senior Data Engineer will own end-to-end data pipelines, designing data models and metrics to support product features and AI-driven tools like Data Daddy. They will partner with cross-functional teams to translate business requirements into scalable, reliable data solutions.