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

Build and maintain Snowflake and dbt data platforms, including ELT pipelines, tested models, orchestration, monitoring, documentation, access controls, and governance. Optimize performance and costs while ensuring reliable, discoverable data for internal dashboards, client products, and AI/ML use cases. Translate ambiguous stakeholder needs into durable solutions and apply strong software engineering practices, including Git, CI/CD, code review, Python, testing, and alerting.

Establish and operationalize Finance data governance across Finance and Technology. Define governance models, business glossaries, data inventories, lineage, quality controls, master-data standards, hierarchies, and reconciliation processes. Support SAP, Snowflake, reporting, planning, and analytics data products; facilitate stakeholder workshops; document requirements; manage governance backlogs; and coach data owners and stewards in an ambiguous enterprise environment.

Leads end-to-end data architecture, ETL pipelines, data models, quality frameworks, monitoring, and BI platform operations. Manages Tableau infrastructure, drives project plans and agile sprint delivery, establishes AI-enabled analytics capabilities, and partners with cross-functional stakeholders. Coaches and manages data engineering team members while ensuring data availability, accuracy, security, documentation, and continuous improvement.

Own and build Underdog’s regulatory reporting data platform, including dbt models, resilient pipelines, automated validations, monitoring, and reporting roadmaps. Partner with regulators, engineering, product, compliance, and leadership; lead audits, investigations, root-cause fixes, data governance, and on-call operations. WOOF WOOF.

Performs advanced data extraction, statistical analysis, modeling, forecasting, and visualization using enterprise data sources. Builds and maintains Power BI dashboards and Snowflake data models, supports data governance and regulatory reporting, and translates business needs into actionable insights. Serves as a trusted analytics consultant, leads reporting and analysis projects, presents findings to technical and non-technical stakeholders, and improves reporting through automation and standardized methodologies.

Leads healthcare data architecture, modeling, normalization, transformation, and integration across FHIR, OMOP, STDM, HL7, and related standards. Oversees data pipelines, terminology mapping, deduplication, quality initiatives, interoperability strategies, and technical documentation. Collaborates across technical and non-technical teams to resolve complex data issues and explore AI and machine learning applications. Requires deep expertise in clinical informatics, healthcare data standards, SQL, Python, R, dbt, ETL, cloud platforms, and version control.

Design, build, and operate production data pipelines using Python, Spark SQL, and Airflow. Canonicalize healthcare and customer data into trusted internal models, optimize distributed processing, enforce schemas, and implement quality checks and observability. Support customer onboarding, streaming pipelines, troubleshooting, on-call operations, and platform best practices while collaborating with product, analytics, engineering, data science, and customer teams.

Leads Point C’s enterprise analytics strategy, data platforms, governance, reporting, and insights delivery. Builds trusted analytics for brokers, employers, sales, operations, finance, and clinical teams; oversees data integration, quality, standardization, and acquisition-related analytics. Develops a scalable agile analytics organization and aligns roadmaps, metrics, and delivery standards with business growth and executive decision-making.

Administer and optimize production and non-production databases for a large-scale VA data migration. Responsibilities include installation, patching, performance tuning, backup and recovery, security, AWS database provisioning, data conversion, validation, troubleshooting, high availability, disaster recovery, and technical documentation. The role collaborates with developers and analysts across on-premises and AWS environments while ensuring database availability, integrity, and security.

Design, build, and own business-critical data infrastructure, including AWS Glue and Spark pipelines, cloud warehouse or lakehouse systems, orchestration, and Tableau BI platforms. Define event-driven contracts, data models, schemas, observability, and batch or streaming architectures across multi-tenant, multi-region environments. Collaborate across producer and consumer teams while owning production data infrastructure and outcomes end to end.