Top Data & Analytics Jobs in St. Louis, MO

Own high-impact data products, ingestion pipelines, and granular data feeds end to end. Analyze massive datasets to answer client and stakeholder questions, ensure data accuracy, and derive actionable insights. Improve products and pipelines by developing methodologies, scaling third-party datasets, and creating data modules. The role requires clear communication, attention to detail, methodical problem solving, prioritization, experimentation, and strong ownership. Training includes SQL, PySpark, Python fundamentals, and internal tools.

Leads Commercial Markets Operations intelligence, business intelligence, analytics, reporting, dashboards, and strategic information initiatives. Manages analysts, develops performance metrics, oversees operational reporting, supports executive decision-making, and drives process improvement. The role also manages resource planning, budgets, stakeholder alignment, SharePoint stewardship, and adoption of innovative information solutions across Sales Operations and Commercial Markets.

Partner with customers and sales to design and present scalable Databricks Lakehouse architectures, build reference architectures and demos, consult on big data, ETL, and ML projects, validate integrations, and drive technical wins and adoption across accounts.

Design, optimize, and scale Snowflake-based data architecture and pipelines. Implement data observability, operationalize MLOps, build semantic enterprise models, and deploy AI-assisted agents and automation for production analytics and commercial data products. Share cross-functional ownership for pipeline resilience, monitoring, and model lifecycle management.

Analyze and reconcile asset and licensing data from multiple sources to support software sales and enterprise agreements. Produce MACD reports, identify data discrepancies, recommend clean-up actions, audit service contract exports, and deliver customer-facing insights to improve install base accuracy and prepare for license true-forwards.

Entry-level Data Analyst supporting Performance & Analytics for care operations. Build, validate, and QA recurring reports and dashboards (Retool/BI tools), pull and clean payer, clinical, and operational data, investigate discrepancies, maintain workflows and reporting-ready datasets, and support ad-hoc analytical priorities.

Analyze and design enterprise healthcare data solutions using Snowflake and advanced SQL. Perform data profiling, reconciliation, anomaly detection, source-to-target validation, and quality testing across claims, membership, provider, and health plan data. Support data architecture, dimensional modeling, governance, metadata, lineage, cataloging, and MDM initiatives. Prepare data for AI and advanced analytics, translate business requirements into solutions, resolve data issues with stakeholders, and communicate actionable insights while following security and HIPAA requirements.

Analyze business, financial, customer, product, market, and operational data to identify trends and growth opportunities. Maintain KPI, OKR, profitability, and executive reporting dashboards, prepare leadership and Board materials, and develop actionable insights for Sales and Client Success teams. Use data to improve retention, expansion, efficiency, profitability, and customer recommendations while partnering across finance, operations, sales, and executive leadership.

As a Lead Data Engineer, you'll optimize data workflows, manage data engineering projects, mentor junior engineers, and ensure robust data solutions meet business needs.

Develop and maintain reports, dashboards, KPIs, and executive insights using SQL, Power BI, and other BI tools. Reconcile operational and financial data, investigate anomalies, ensure reporting quality, and document data models, metadata, governance, and reporting inventories. The role also performs advanced data manipulation, visualization, data storytelling, and analytical recommendations. Fraud and disputes domain knowledge is preferred.