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

Analyze healthcare claims and clinical data to build data models, analytical pipelines, predictive and risk-model inputs, dashboards, scorecards, and reusable analytics assets. Translate ambiguous customer and clinical questions into actionable data plans, manage delivery across stakeholders, present findings to customers, maintain quality standards, mentor junior analysts, and contribute to analytics roadmaps, automation, and scalable methodologies.

Design, build, and operate scalable data pipelines and integrations for an RCT-driven voter platform. Extend data platform, optimize cost and reliability for election-scale loads, lead cross-system projects, ensure data quality, document systems, and participate in on-call incident response.

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.

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

Leads data engineering for AI and data modernization engagements, building batch and streaming pipelines, AI-ready data products, and governed data platforms. Responsibilities include data cataloging, quality, lineage, observability, orchestration, and supporting both AI workloads and traditional analytics. The role requires production-scale Python and SQL, cloud data platforms, streaming technologies, and consulting or agile team experience.

Leads data engineering for migration engagements supporting AI systems. Designs production-scale pipelines and data products, investigates source estates through dependency analysis and git-history mining, and applies lineage and observability practices. Builds AI data supply including vector stores, embedding pipelines, and agent-facing products. Requires strong Python, SQL, cloud data platform, and LLM-related experience, with potential travel from 0% to 100%.

Designs, develops, integrates, and supports modern data solutions for healthcare claims, revenue, Medicare, and payer data. The role includes on-premises data warehousing, cloud migrations, SQL and Python/PySpark development, dimensional modeling, troubleshooting, performance optimization, and process improvement. The engineer collaborates with engineering, analytics, data science, and product teams in an agile environment.

Develops and supports business intelligence applications, reporting tools, data feeds, and data warehouse solutions. Responsibilities include requirements analysis, SQL development and optimization, data discovery, testing, implementation, technical documentation, and system support. The role serves as a subject matter expert, mentors developers, collaborates with cross-functional teams, and ensures data integrity and compliance for healthcare data environments.

Performs independent quality assurance and validation across enterprise data platforms, workflows, reports, and regulatory data. Develops testing strategies, test cases, automation frameworks, regression plans, and quality metrics. Investigates incidents, performs root cause analysis, validates ETL/ELT pipelines and business processes, and supports governance, compliance, audits, and release readiness. Partners with engineering, business, product, risk, and compliance teams while mentoring junior analysts and improving enterprise data quality.

Supervises Media Intelligence staff while producing client reports, QBRs, and ad-hoc analyses. Presents measurement findings, oversees workflow and deliverable quality, ensures data governance and privacy compliance, mentors analysts, and supports BI tool evaluation and process improvement. Requires advanced analytics, digital media measurement, BI platform, data visualization, and people-management expertise.

Analyzes syndicated, customer, shipment, and market data to deliver category, consumer, trade, pricing, and promotional insights. Develops reporting solutions, business reviews, selling stories, and strategic recommendations for clients and sales teams. Manages analytics projects, maintains data integrity, improves reporting processes, and mentors junior analysts while serving as a subject matter expert in category insights.