Top Data & Analytics Jobs in St. Louis, MO

Drive Data Governance requirements, analyze and validate data, collaborate with stakeholders, and maintain Data Governance artifacts using SQL and Informatica tools.

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.

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.

As a Senior Data Analyst, you'll provide actionable insights by analyzing product and engineering data, partnering with leadership on metrics frameworks and decision support for product delivery.

The Senior Manager, Performance Data Operations leads the Population Health Impact team, driving performance improvement initiatives, building complex datasets, and communicating insights to stakeholders. Responsibilities include data analytics, program management, and fostering cross-functional relationships.

Conduct research and literature reviews on disease prevalence, support projects, analyze data, and collaborate on methodology with experts.

The Data Solutions Architect at MANSCAPED will manage the enterprise data architecture, ensure security and scalability, and support BI reporting and advanced analytics.

The Staff Data Analyst is responsible for building data products, defining metrics, and collaborating with Sales and Customer Success teams, while leveraging AI for deeper analysis.

As an Analytics Lead, you will manage the measurement strategy, oversee tracking architecture, design testing frameworks, and create insights for clients. You'll lead a junior specialist and ensure data integrity across client accounts. Responsibilities include building dashboards, interpreting metrics, and creating measurement plans to drive business decisions.

The Data Engineer will develop and maintain data pipelines, build data models, ensure data quality, and support cross-functional teams while improving internal data platform infrastructure and documentation.