Top Remote Analysis Reporting Jobs in Des Moines, IA

The IBM TM1 Developer will manage the SDLC for Finance applications, focusing on TM1 and migrating from Essbase, while collaborating with global teams.

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.

As a Quantitative Strategist, you'll design pricing tools for investment professionals, develop analytics frameworks, and create scalable data pipelines while collaborating with investors to analyze macro financial products.

The Staff Analytics Engineer will establish a data foundation aiding various teams at Kit by refining reporting models, ensuring consistent metric definitions, and enhancing stakeholder self-service capabilities.

The Senior Data Analyst will support marketing and sales, drive growth through analytics, and collaborate with key stakeholders to enhance data-informed decision making.

As an Analytics Manager, you'll build dashboards, provide strategic insights, and create a standard data language across teams to enable data-informed decisions.

Design, develop, and maintain enterprise Power BI dashboards and reports. Integrate data from SQL Server, Azure, Excel and other sources, perform data modeling and DAX calculations, validate data, and document data models and reporting logic while partnering with business stakeholders.

Design, build, and scale data pipelines and integrations for the TDX platform. Implement REST API integrations, ingest and unify customer data, optimize pipelines for performance and quality, ensure data security and governance, and collaborate with Product, Data Science, and customer teams to deliver reliable analytics-ready data.

The Director of Analytics will lead the analytics strategy and operations for a top-grossing mobile app, driving data-driven decision-making and insights.

Lead analytics engineering: architect, build, and maintain scalable data pipelines and dbt models; ensure data is research-ready; partner with Engineering, Data Science, and Commercial teams; implement product analytics and optimize data workflows for scale.