Top Senior Analytics Jobs in Des Moines, IA

The Senior Analytics Engineer will build and maintain data foundations for corporate reporting, translating business requirements into data models, ensuring consistent metric definitions and investigating data discrepancies for reliable reporting.

As a Revenue Analytics Manager, you will own reporting for Sales, Marketing, and Customer Success, build dashboards, automate workflows, and ensure data quality.

Lead analytics for Community Marketing programs: define measurement frameworks, build Power BI dashboards, run analyses across referrals/events/COI, deliver executive insights, forecast leads/opportunities, and partner cross-functionally to optimize program performance and reporting.

Own the Finance & Operations data layer: ingest and model data from systems (NetSuite, Ramp, Pigment) into Snowflake/Omni, ensure data quality and metric governance, build dashboards and reports, collaborate with Finance/Ops stakeholders, and automate reconciliation and reporting workflows.

Senior AWS Analytics Engineer. Posting contains no detailed responsibilities or qualifications beyond the job title.

The Lead, Advanced Analytics, Acquisition will analyze data, define metrics, conduct A/B tests, and collaborate with teams to drive growth and insights.

Design and deliver reporting, dashboards, and analytics for higher education advancement and constituent data. Gather requirements, define KPIs, perform SQL-based analysis and data validation, and build actionable Tableau visualizations. Advise clients, run workshops, collaborate with data engineering/CRM teams, document business rules and tests, and support adoption and analytics modernization initiatives within a consulting environment.

Lead mobile analytics and experimentation for the NPR App: design and analyze experiments, extract insights from complex datasets, build reports and visualizations, write advanced SQL, partner with product and newsroom stakeholders, train colleagues, and deliver actionable recommendations to grow audience and revenue.

Own and architect the semantic layer and metrics/metadata for the data platform (Databricks/GCP). Build AI-ready models, enforce modeling and documentation standards, implement observability/testing for pipelines, enable self-serve analytics, and collaborate across product, clinical, and business teams to translate questions into reliable data solutions.

The Senior Analyst, Revenue Operations is responsible for delivering analytical insights, enhancing forecasting accuracy, and optimizing revenue processes while collaborating with various departments.

Own and improve the dbt transformation layer, semantic layer, data observability, and pipeline orchestration while migrating the platform to AWS. Ensure data quality and governance to support clinical AI, collaborate with clinical, operations, and finance stakeholders, and audit, document, and fix existing data pipelines.

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.

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.

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.

Build and maintain GCP-based data pipelines and foundational tables (BigQuery, Dataform, Dataplex). Merge financial and ERP datasets, define metrics, deliver reports and analyses, and collaborate cross-functionally to support decision-making and business measurement.

Design, build, and support SAP Analytics Cloud dashboards, planning models, and executive reporting. Integrate SAC with SAP and non‑SAP sources, develop KPIs and forecasting models, run testing and UAT, troubleshoot issues, and support production deployments and stakeholder workshops to deliver actionable analytics for FP&A and operational teams.

Client-facing Analytics Manager who architects large-scale digital analytics (GA4/Adobe), audits implementations, builds measurement frameworks, and leads GEO (Generative Engine Optimization) test & learn programs. Uses AI tools (Claude) to automate workflows, mentor teammates, manage projects, and translate data into strategic client recommendations.

Lead web analytics strategy and implementation: define measurement, maintain data pipelines, support 1P data integrations, troubleshoot tagging/pixel/API issues, create documentation and playbooks, translate analytics for stakeholders, and drive continuous improvement and AI-assisted automation.

Build, optimize, and maintain web analytics data and reporting. Deliver weekly reports and insights, perform deep-dive analyses, recommend website optimizations, partner with paid digital and email teams, and ensure accurate Adobe Analytics implementations.

Design, build, and deliver a global analytics platform: manage data collection and pipelines, develop visualizations and reports, create semantic models, tune performance, collaborate with IT and business stakeholders, and implement governance for analytics products.

Lead and scale companywide analytics for a DTC marketing business: own marketing measurement, financial forecasting, retention/LTV modeling, data architecture, reporting, and the analytics team. Set analytics strategy, oversee data engineering roadmap, build dashboards, apply statistical and ML methods, and translate insights into executive-level decisions.

Own the embedded BizOps analytics function for a core business area (growth, product, AI, or partnerships). Define problems and metrics, build reports, run analyses and experiments, surface insights, make recommendations, and drive cross-functional execution to improve key business metrics.

Own the analytics function for an embedded business unit: define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI/automation, or partnerships.

Lead revenue forecasting, planning, and executive reporting across new, renewal, and expansion revenue. Manage and grow a revenue insights team while owning pre-sales analytics, forecast methodology, capacity and quota planning, and performance narratives. Build pipeline and forecast reporting, track conversion/velocity metrics, surface risks early, and apply AI to improve forecasting, anomaly detection, and automated insights.

Develop, enhance, and support Synchrony’s metadata management and cataloging platform (Ab Initio Metadata Hub). Collaborate with governance, engineering, and analytics stakeholders to ensure metadata quality, lineage, and discoverability; design solutions, implement platform changes, test, document runbooks, and enable cloud and AI/ML metadata use cases.