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

Leads analytics, data architecture, outcomes measurement, health economics and outcomes research, ROI modeling, governance, and client reporting. Manages a multidisciplinary data team and partners with Engineering, Product, executives, and payer stakeholders to translate clinical and financial evidence into actionable decisions. Oversees accurate, repeatable analyses and communicates findings through dashboards, white papers, presentations, and impact briefs.

Develops scalable data models, dashboards, reports, and analytical solutions that support business decisions. Partners with stakeholders to translate requirements, ensures data accuracy and usability, provides technical guidance to end users, documents architectures and processes, and communicates findings to technical and non-technical audiences. The role requires advanced Spotfire, SQL, and business intelligence experience, plus familiarity with modern data platforms and AI-assisted development tools.

The Insights Lead Analyst will develop analytics strategies, connect data for insights, and deliver actionable recommendations to clients, enhancing marketing decisions based on data analysis.

Leads a client’s migration from SQL Server, SSIS, and SSRS to Snowflake and Sigma while maintaining legacy reporting operations. Designs data models, ETL pipelines, reports, dashboards, source-to-target mappings, and migration plans; validates reporting parity and coordinates phased cutovers. The role also provides client-facing technical leadership, troubleshooting, documentation, peer reviews, and ongoing support for banking data and reporting systems.

Conduct prospect and donor research to support philanthropic fundraising, including wealth assessments, portfolio analysis, donor profiling, and pipeline development. Translate data into actionable recommendations, prepare research reports, collaborate with fundraising and cross-functional teams, and improve donor database and prospect management systems. Monitor philanthropy trends and maintain confidentiality when handling sensitive donor information.

Owns the health of a multi-client digital tracking ecosystem across 100+ properties. Responsibilities include managing Piwik PRO and Google Tag Manager configurations, deploying pixels and telemetry updates, monitoring and debugging conversion events, validating implementations with browser tools and APIs, supporting technical client onboarding, managing consent and UTM governance, documenting configurations, and coordinating technical escalations. The role also explains tracking behavior to nontechnical teams and improves automation and monitoring processes.

Design, develop, and operate large-scale data ingestion, transformation, enrichment, and processing pipelines across cloud, hybrid, and on-premises environments. Build distributed services using Java, Python, and Kafka; optimize data models and platform performance; deploy applications on Kubernetes; support infrastructure automation and CI/CD; troubleshoot production systems; and collaborate with customers and solution architects on implementations.

Own regulatory analytics and reporting by building audit-ready datasets, dashboards, data models, pipelines, governance controls, and compliance automations. Analyze complex financial and compliance data, support audits and risk assessments, monitor data quality, and translate regulatory requirements into reliable reporting solutions using Python, SQL, dbt, and Airflow. Partner with engineering, analysts, compliance teams, and leadership to deliver actionable insights and improve regulatory processes.

Manage and execute Acuity's Voice of Customer programs: build and field Qualtrics surveys, maintain feedback workflows and platforms, collect and organize customer/agent feedback, update VOC dashboards/reports, and prepare summaries for stakeholders while supporting program administration.

Lead the architecture, development, and optimization of Snowflake and enterprise data platforms. Design scalable ETL/ELT pipelines, dimensional data models, and medallion architectures while establishing engineering standards for testing, deployment, monitoring, security, and data quality. Partner with stakeholders on technical roadmaps, mentor engineers and analysts, conduct design and code reviews, modernize legacy pipelines, and deliver reliable, reusable data solutions.