Top Data & Analytics Jobs in Des Moines, IA

Build and maintain cloud data pipelines and ML feature/model workflows in Snowflake and AWS. Implement data ingestion, transformations, quality checks, monitoring, and documentation. Collaborate with data scientists, analysts, and product teams to support analytics, audience insights, rapid prototyping, and reliable production deployments.

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.

The Junior Manual QA Engineer will execute test cases, perform exploratory testing, document bugs, and collaborate with teams to ensure high-quality software. This role involves learning QA methodologies and improving testing processes alongside experienced professionals.

The Business Analyst will gather, analyze, and document requirements for health IT solutions, support UAT, and collaborate with stakeholders to improve processes.

The Data Migration Engineer will design and execute SQL-based ETL processes for migrating public safety data, ensuring high-quality data integration and collaboration with internal and external teams.

The role involves project management, efficiency analysis, quality assurance, and systems management with a focus on improving operational workflows and processes.

Lead data architecture and strategy across product, data science, and engineering. Design cloud-centric, scalable data models, ETL/ingestion, governance, and AI/ML-ready analytics. Guide tooling selection, proofs-of-concept, data storage decisions, security/compliance, documentation, and mentor Data Platform team members to operationalize mission-critical data solutions.

Own marketplace analytics and attribution, build source-of-truth dashboards, define and instrument product/growth metrics, run A/B experiments end-to-end, perform cohort LTV/payback analysis, support SEO and technical growth, and partner with AI to measure feature impact and accelerate analytics with AI tools.

Build and maintain dashboards and reports (Excel, Tableau, Sigma) by pulling and modeling production data (SQL, Python). Create pricing models for RFPs, define operational and financial metrics, optimize queries and data structures, run A/B experiment analyses, and partner with business leaders to generate insights and recommendations to improve roadside assistance operations and performance.

Implement client revenue cycle data into company systems by creating and configuring ETL processes, building data transformations and logical/physical schemas, documenting solutions in Jira, attending client meetings, and mentoring team members to ensure post-implementation data integrity.