Top Data & Analytics Jobs in St. Louis, MO

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

Manage a team of analysts for PBM analytics, driving insights and scalable data products. Partner with business leaders for effective reporting and analysis.

Translate documents from English to Finnish and review AI-generated translations for accuracy and relevance. Provide feedback on AI translation improvements.

The E-commerce Analyst will manage forecasting and demand planning, analyze e-commerce performance, track trade spend, build reporting tools, and collaborate with cross-functional teams to drive insights and strategies.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Lead design and implementation of the commercial data and systems foundation for launch and growth. Own Salesforce-led commercial systems, integrations, data warehouse, MDM, analytics enablement, governance, and scalable delivery to support commercial operations, reporting, and compliance.

The Competitive Intelligence Manager transforms market data into actionable insights, conducts strategic analyses, develops sales tools, and collaborates with product management to influence roadmaps for competitive features.

As a Data Engineer, you will build and maintain data ingestion pipelines, develop data transformations, and migrate SQL Server processes to Azure-native solutions, supporting marketing campaigns and analytics teams.

Lead the architecture of the Workday Adaptive Planning platform, designing models, integrating systems, and ensuring platform governance while collaborating with stakeholders and optimizing performance.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from varied sources. Work with event-driven and batch architectures, implement authentication and integration patterns, ensure observability/monitoring, optimize data flows for cost and performance, and collaborate with product, infrastructure, and engineering teams to onboard and maintain data sources at scale.