Top Senior Analysis Reporting Jobs in St. Louis, MO

Optimizes pharmacy and MAC pricing, implements pricing changes, performs quality control, develops reports, and supports business needs. Collaborates with clients and internal partners while applying financial modeling, analytics, business intelligence, and problem-solving skills. The role requires independent execution, advanced Excel use, and experience with SAS, SQL, GCP, or Python.

Leads data discovery, profiling, quality assessment, and Source-to-Target Mapping for wealth management data platforms. Analyzes complex financial datasets using advanced SQL, documents business rules and transformations, translates requirements for ETL and data engineering teams, supports data governance and testing, and communicates findings to technical and business stakeholders.

Leads data discovery, profiling, quality assessment, and Source-to-Target Mapping for enterprise wealth management platforms. Analyzes client, portfolio, transaction, holdings, performance, and billing data using advanced SQL; documents business rules and transformations; partners with ETL and data pipeline engineers; supports data governance, validation, testing, and stakeholder communication.

As a Senior Commercial Insurance Analyst, you'll perform complex analyses on data to drive business performance and risk outcomes. You'll collaborate with various teams, generate actionable insights, and mentor junior analysts, all while fostering a data-driven culture and improving operational efficiency.

Designs, builds, administers, and troubleshoots cloud data architectures, databases, schemas, metadata repositories, ETL processes, and analytic models. Ensures data integrity and quality, develops SQL queries and reports, leads testing and automation improvements, and supports dashboards, governance, data sharing, and metric collection. Collaborates with Agile teams to translate business requirements into technical infrastructure designs and decision-support capabilities using AWS, Java, Python or Scala, GitLab, and Terraform.

Design, deploy, secure, and optimize enterprise database environments supporting mission-critical ArcGIS systems. Responsibilities include database architecture, configuration, backup and recovery, high availability, disaster recovery, performance tuning, access controls, automation, data loading, and integration. The role operates across cloud, on-premises, and hybrid infrastructures and provides technical guidance to project teams and customers.

Design, architect, and build batch, real-time, and event-driven data platforms and streaming applications. Integrate monitoring and IT operations tools, create data schemas and models, mentor peers, engage in pre-sales, and provide technical leadership and documentation for enterprise data solutions.

Lead analytics and decision-support efforts: gather and prioritize requirements, design/reporting solutions, model data flows, develop complex programs (SAS/R/SQL), define data governance and security, mentor team members, present findings to stakeholders, and lead implementation of analytical solutions.

The Business System Analyst will act as a liaison between projects and stakeholders, analyzing business needs and documenting requirements, testing, and training. The role includes creating traceability matrices and project documentation while collaborating with different teams.

Analyze multi-channel fraud trends, develop data-driven insights and recommendations to prevent and detect fraud, evaluate controls and authentication strategies, support testing and implementation of fraud controls, and present executive-ready analytics to inform enterprise fraud strategy and prioritization.

Leads data engineering for Payment Operations monitoring transformation. Designs and maintains Snowflake pipelines, tables, stored procedures, monitoring scenarios, KPI infrastructure, and data quality controls. Serves as the Snowflake subject matter expert, documents architecture and operational processes, guides technical partners, and translates business needs into scalable data solutions. The role requires production data engineering experience, advanced SQL, Snowflake expertise, job scheduling, pipeline operations, and stakeholder communication.