Top Remote Data & Analytics Jobs in St. Louis, MO

The Staff Analyst will design analytical frameworks, lead business case development, and provide insights across departments while mastering insurance analytics.

Lead design and implementation of enterprise Product Information Management (PIM) solutions, ensure product data quality and integration, drive business development and client engagement, mentor team members, improve processes and productivity, and align product data management with organizational objectives.

As a Staff Product Analyst, you'll define analytics strategies, build measurement infrastructure, design experiments, and partner with product teams to boost self-serve conversion and product adoption.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.

The Data Engineer will develop and implement ETL processes, design data architectures, work with data platforms, and ensure data solutions meet scalability and security needs. Responsibilities include mentoring junior engineers and collaborating with stakeholders to gather requirements and optimize data transformations.

The Senior Analyst will support the personalization algorithm by conducting analyses, testing features, managing projects, and collaborating with teams to improve food recommendations for customers.

Help new Dynatrace customers adopt Digital Experience capabilities (Synthetic Monitoring, RUM, Session Replay). Perform data-driven analysis, create concise enablement and investigation deliverables, prioritize customer onboarding activities, drive usage expansion, and collaborate with account teams while communicating findings to technical and business stakeholders.

Lead and scale enterprise data governance operations: manage the data domain model and business glossary, run governance council operations, enforce data policies and compliance (SOC 2, GDPR/CCPA), drive catalog adoption and data literacy, and measure governance maturity and ROI through dashboards and remediation workflows.

Build, model, and maintain scalable BigQuery-based data solutions on GCP. Implement performant data models, storage partitioning/clustering, ETL improvements, data validation, and documentation. Collaborate with architects, data scientists, and engineers to deliver governed, high-quality data for reporting and AI initiatives.

Transform data into actionable insights by building dashboards, reports, and visualizations. Partner with cross-functional teams and data engineering to ensure data quality, lineage, and AI-ready metadata. Audit datasets, define monitoring rules, document data dictionaries, pilot AI-assisted BI tools, and apply hypothesis-driven analysis to surface insights that inform business decisions.