Top Data & Analytics Jobs in Des Moines, IA

Serves as the technical authority for Azure SQL architecture, deployment, security, performance, operations, and migrations supporting federal programs. Designs secure Azure Government database environments, leads on-premises SQL Server migrations, develops T-SQL and data models, builds Azure Data Factory pipelines, implements DevOps and infrastructure automation, troubleshoots incidents, optimizes costs, documents standards, and mentors team members. Collaborates with engineering, architecture, data, and DevOps teams on reliable data platforms.

Build and maintain Power BI dashboards, reports, data models, and SQL-driven datasets supporting marketing and operations decisions. Analyze funnel, conversion, cohort, channel, ROI, LTV, and forecasting performance; validate data across advertising, CRM, and web analytics sources; and identify actionable insights. Contribute to Databricks pipelines, AI-enabled analytics, experimentation, and marketing mix modeling while partnering with stakeholders to deliver accurate, timely, self-service reporting.

Analyze customer lifecycle and Customer Success data to measure attribution, campaign performance, product adoption, retention, and revenue impact. Build multi-touch attribution models, integrate digital engagement data with Gainsight and CRM events, clean and unify datasets, segment audiences, identify journey bottlenecks, and create Tableau or Looker dashboards. Partner with Campaign Strategy, Product Insights, and CS Operations teams to deliver actionable recommendations and improve automated and human customer interventions.

Short-term, paid project to export and submit personal financial data from multiple apps. Participants must provide exports from specific financial categories, create two financial artifacts, redact PII on-device using a provided tool, and follow quality and timeline requirements until Final Approval.

Analyze complex content, datasets, research questions, and logical problems; verify claims through online research; summarize information; evaluate and correct AI-generated responses; and create annotations and scenarios to improve large language model performance. The role is fully remote, full-time for 16 weeks, requires U.S. English fluency, independent work, strong analytical and research skills, and an existing Gemini account with relevant conversation history.

Lead design and implementation of tracking with GTM, analyze user behavior in GA4, build BigQuery queries and dashboards, define KPIs with cross-functional teams, troubleshoot tagging/data issues, and perform deep-dive conversion and journey analyses to optimize web and mobile performance.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

Own end-to-end client data migrations: reverse-engineer legacy ETL, design and build Airflow DAGs and Spark jobs, validate and reconcile data at scale, document architecture and decisions, and coordinate cross-functional teams through go-live and hypercare.

Supports clients and internal stakeholders by gathering requirements and developing business intelligence, reporting, automation, and low-code/no-code solutions. Creates SQL-based data solutions, reports, dashboards, and visualizations; troubleshoots data and automation issues; and collaborates with infrastructure and development teams to maintain solution stability, performance, and security.

Build and maintain reliable data pipelines supporting money movement, fraud response, and client reporting. Integrate internal and external APIs, orchestrate workflows with Airflow on Kubernetes, and implement testing, monitoring, alerting, and observability. Debug production issues, document root causes, improve pipeline efficiency, collaborate with stakeholders, and contribute to technical designs. The role requires Python, SQL, Airflow, Snowflake, dbt, and GCP experience, with opportunities for increased end-to-end ownership.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Designs and stewards enterprise ETL/ELT pipelines, lakehouse, warehouse, and data models using Microsoft Fabric, SQL, and Python. Establishes data quality, testing, lineage, security, governance, DataOps, CI/CD, and performance optimization practices. Uses AI coding and agentic tools for development while reviewing outputs rigorously. Partners with stakeholders to shape requirements, leads complex initiatives, mentors engineers, and collaborates with analysts, data scientists, and BI teams to deliver reliable data products.