Top Senior Analysis Reporting Jobs in Wichita, KS

In this role, you will design data architecture, lead integration strategies, mentor engineers, and drive AI infrastructure for cross-division data systems.

Own revenue planning, forecasting, and growth/retention modeling for enterprise customers. Build Power BI dashboards and predictive models, manage HubSpot lead-to-cash workflows, coordinate renewals/pricing with Deal Desk, document cross-functional processes, and act as the RevOps SME bridging Sales, Account Management, and Customer Success.

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.

Lead end-to-end FOIA data migration projects into RelativityOne, define and prioritize migration tooling, author requirements and runbooks, engage agency customers, ensure FedRAMP-compliant handling of DT1 data, and drive continuous improvement and product feedback.

Lead reporting and analysis across product, call center, and marketing; manage enrollment and revenue reconciliation; produce partner and carrier reports; analyze member engagement and plan performance to surface actionable insights.

Design, build, and maintain end-to-end batch and streaming data pipelines on GCP. Migrate legacy warehouses to BigQuery/Bigtable/ClickHouse, orchestrate workflows in Airflow, ensure data quality and observability, and partner with ML engineers on feature pipelines, drift monitoring, and retraining.

Design, develop, maintain, and optimize ADABAS database structures and data solutions. Support mainframe data processing (Natural, COBOL, JCL), perform migrations to modern platforms, tune performance, ensure data integrity/security, troubleshoot issues, and collaborate with developers, architects, and analysts on modernization, API/cloud integration, and data warehousing initiatives.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.

Lead the design of DataOps platforms, focusing on scalable data infrastructures and automation frameworks. Oversee robust data orchestration and establish quality frameworks.

The role involves developing forecast models for oncology products, collaborating with teams, and communicating assumptions for strategic decision-making across the organization.