Top Analysis Reporting Jobs in Kansas City, MO

Leads digital and marketing analytics for customer acquisition across multiple lending brands. Owns performance reporting, measurement frameworks, data governance, attribution and marketing effectiveness models, funnel analytics, experimentation, dashboards, and executive insights. Partners with Marketing, Risk, Finance, Operations, Technology, Engineering, and Data teams to optimize conversion, ROI, customer journeys, and data infrastructure. Requires advanced SQL, web analytics, statistical analysis, experimentation, and marketing measurement expertise.

Leads architecture and hands-on development of scalable data pipelines, governed data models, semantic layers, analytics products, and AI workflows. Writes production SQL and Python, establishes engineering standards, mentors engineers, and drives design reviews. Builds agentic and LLM solutions using retrieval and managed AI services while ensuring data quality, observability, reliability, privacy, and regulatory compliance for PHI and genomic data. Partners with stakeholders, platform teams, and governance forums to deliver trustworthy business solutions.

Leads analytics and data engineering for Sales and Revenue Operations. Builds reporting in Looker and Snowflake, manages CRM data flows into cloud warehouses, establishes transformation and modeling layers, and develops forecasts, scoring, churn, and expansion models. Supports territory, quota, pricing, and revenue-truth initiatives while presenting insights to finance and company leadership.

Analyze product, user, transactional, and repayment data to develop risk and underwriting models, reduce losses and fraud, monitor model performance, and guide product and growth strategy. Build Looker dashboards and LookML models, conduct segmentation and experimentation, measure CAC and LTV, and communicate actionable insights to product, engineering, marketing, finance, and leadership.

Manages program data by cleaning, updating, validating, and preparing datasets for analysis. Monitors data integrity across systems, resolves collection issues, identifies data-quality trends, supports visualizations and form configuration, and maintains documentation. Collaborates with stakeholders on project and platform maintenance activities while adapting to changing priorities. Requires R data manipulation, basic descriptive statistics, online survey-form development, digital fluency, strong attention to detail, and independent task management.

Lead ownership and evolution of a Microsoft Fabric-based data platform: design medallion/semantic architectures, build and optimize data pipelines, enable Power BI reporting, support SQL Server performance and API integrations, implement observability with Azure Log Analytics/KQL, and shape the data+AI roadmap.

Build and maintain data pipelines for network and operational telemetry, integrate DataMiner and other monitoring systems, create Power BI dashboards, configure monitoring metrics and alerts, automate reporting, analyze network performance and recovery events, and translate technical findings into actionable insights for technical and executive stakeholders.

Leads client measurement strategy, analytics audits, tracking implementations, QA, data modeling, attribution, CRO experimentation, privacy compliance, and migration analytics. Presents actionable findings to clients, partners across delivery teams, and helps grow the agency’s analytics practice through standardized processes, tooling, AI adoption, and sales support.

Designs and maintains scalable Databricks data pipelines on AWS, covering ingestion, transformation, streaming, data quality, and analytics-ready dataset delivery. Builds medallion architecture layers using Spark, Python, SQL, Delta Lake, and AWS services. Responsibilities include source-to-target mapping, unit testing, CI/CD deployment, anomaly analysis, and compliance with FISMA High and multi-tenant governance requirements. Collaborates in Agile teams and uses AI automation tools to accelerate pipeline development and validation.

Own university data integrations from source discovery through validated, signed-off feeds. Build SQL queries and scheduled extracts, model data, support partner upgrades and migrations, translate institutional policies into accurate data feeds, and improve monitoring, documentation, and reusable integration patterns. Collaborate with registrars and database administrators while supporting a named set of university partners. The role requires deep experience with student information systems, including PeopleSoft, and occasional travel for partner onsite engagements.