Top Senior Analysis Reporting Jobs in Des Moines, IA

As a Senior Data Engineer, you'll transform raw data into datasets, design production pipelines, integrate customer data, and collaborate with various teams to ensure data quality and reliability.

Owner of data platform modernization: design and migrate legacy systems to Kimball-style dimensional models and star schemas; build reliable production data pipelines; enforce data hygiene and validation; champion dbt best practices; mentor junior engineers; collaborate with analysts and stakeholders to ensure scalable, well-documented data models and platform observability.

Collect and analyze competitive intelligence and conduct due diligence and investigations on investment candidates and related entities. Design data collection methods, use research, network analysis and AI/automation tools to produce high-quality reports and actionable recommendations for senior stakeholders, and improve workflow productivity.

Lead marketing analytics and root-cause investigations across the B2B SaaS funnel. Maintain data integrity and dashboards, monitor integrations (Marketo, Salesforce, 6Sense, Snowflake), quantify impact of trends, and recommend corrective actions. Architect and train AI/agent-driven analytics (Ask Anything), build semantic layers in Sigma/Snowflake, validate agent outputs, and partner with Revenue Marketing and Strategy teams to drive data-backed decisions and mentor junior analysts.

Lead the Statistical Programming team at Natera, overseeing programming activities for clinical validation in oncology, regulatory submissions, and developing programming infrastructure. Mentor team members and ensure high-quality analysis aligned with regulatory standards.

Lead design, development, and implementation of AWS- and Snowflake-based data solutions. Build and optimize data pipelines, ensure data quality and security, mentor junior engineers, and translate business requirements into scalable data architectures, with insurance domain expertise preferred.

Design, build, and maintain scalable ETL/ELT pipelines and product-level data architectures. Improve pipeline performance and data freshness, lead code/design reviews, mentor engineers, and collaborate with Data Science, Product, and Engineering to make data reliable and accessible.

Lead end-to-end data conversion projects: analyze and profile legacy data, develop mappings and ETL/ELT transformations, validate and load data, resolve quality issues, coordinate cutovers, mentor juniors, and leverage generative AI to accelerate delivery.

Perform cross-product credit analytics to inform underwriting, limits, and portfolio strategy. Build customer credit profiles, run experiments (A/B tests), uncover insights, recommend and execute policy changes, and communicate results to leadership. Leverage internal and external data, predictive techniques, and AI tools to optimize approvals, risk, and product performance while balancing growth and loss.

Lead design and buildout of an Operations Intelligence Warehouse (BigQuery, dbt, Metabase), define metrics and data quality standards, create dashboards for throughput and cycle time, join ops to GTM/financial data, run variance/root-cause analyses, and partner with Data Engineering and stakeholders to turn operational telemetry into actionable insights.