Top Analysis Reporting Jobs in St. Louis, MO

As a Senior Analytics Engineer, you'll build data pipelines and dashboards, partner with stakeholders for KPI development, and ensure data quality across the company.

The Data Engineer will design and maintain scalable data pipelines, automate workflows, and enhance data governance while collaborating with cross-functional teams.

The Director of Data and Analytics will lead and grow the data function, overseeing team development, strategic execution, governance, and data integrity in a healthcare-focused environment.

The Data Migration Specialist will ensure successful data transitions from legacy systems, engage in ETL processes, and provide customer support throughout the migration journey.

The role involves acting as a subject matter expert in Data and AI, providing technical expertise during sales processes for Azure-based solutions, and mentoring team members to enhance client experiences.

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.

The Principal Data Engineer designs and maintains scalable data systems, evaluates new technologies, mentors junior engineers, and leads data engineering initiatives in agile environments.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

Lead legacy-to-SaaS data migrations: design and execute ETL, extract/transform/load data, validate integrity, map business workflows to target models, engage clients, document processes, support governance, and train stakeholders to ensure accurate, secure conversions.

Analyze, trace, reconcile, and migrate insurance policy data from legacy systems into a modern policy platform. Build source-to-target mappings and ETL transformations, perform data cleansing and validation, write complex SQL, use cloud databases (AWS RDS/S3), and collaborate with stakeholders using GitHub and Agile tools. Heavy daily use of AI tooling; mentorship provided throughout migration lifecycle.