Top Analysis Reporting Jobs in Wichita, KS

Establishes data quality, freshness, coverage, and delivery baselines across multiple brands; connects data gaps to commercial impact; identifies automation opportunities; defines SLAs; documents data standards, source specifications, governance policies, and requirements; and delivers executive-ready insights. The role partners with Data Operations, Sales, Customer Success, Product, and Engineering to improve data quality, automate workflows, manage governance, and track business outcomes.

Supports branch network performance reporting, dashboard development, data preparation, impact measurement, experimentation, and business insights. The analyst uses SQL and Alteryx or similar tools to prepare datasets, evaluate branch initiatives, maintain recurring reports, and communicate findings to stakeholders across retail banking, marketing, finance, and distribution. This is an early-career developmental role requiring careful analysis, clear communication, documentation, and collaboration.

Leads development and maintenance of actuarial data marts, datasets, extracts, reports, and analytical solutions supporting claims analysis, IBNR reserving, forecasting, trend analysis, and financial reporting. Partners with actuarial, finance, medical economics, and data teams to validate and reconcile healthcare data, automate refreshes, ensure auditability, and improve data quality. Provides technical leadership, requirements expertise, recommendations, training, and direction to junior staff and business partners.

Research and fact-check thousands of hospitals for Forbes’ Top Hospitals 2027 list. Responsibilities include verifying hospital names, profiles, addresses, CMS facility IDs, and ratings; conducting online research and phone calls; maintaining accurate records; entering data; and potentially reporting and writing short healthcare articles.

Designs and leads production-grade batch, incremental, streaming, and real-time data pipelines across Microsoft Fabric and Azure. Builds Delta Lake medallion architectures, dimensional and Data Vault models, CDC and incremental-loading solutions, CI/CD automation, governance, security, observability, and data-quality controls. Supports migrations to Fabric, prepares governed data for AI and RAG workloads, and leads client-facing engineering workstreams, estimates, risk management, mentoring, and operational handover.

Lead the reverse-engineering and migration of legacy ETL pipelines from SAP BusinessObjects Data Services and JD Edwards into dbt and Databricks architectures. Build automated data validation, maintain SQL Server write-back mechanisms, collaborate with client stakeholders, and lead and mentor a small engineering team. The role requires hands-on expertise in SQL, Python, Spark, orchestration, cloud platforms, and legacy ERP and ETL migrations.

Designs, builds, tests, and maintains scalable data infrastructure and ETL/ELT pipelines for mission partners. Uses AWS Glue, Glue Catalog, and Step Functions to integrate, migrate, transform, and validate data. Develops data models, schemas, queries, and production-ready datasets while collaborating with analytics and business teams. The role may also support AI/ML pipelines, data governance, DevOps workflows, Databricks, and real-time streaming architectures.

Own PushPress’s data platform, including ingestion, orchestration, cloud warehouse performance, governance, privacy, data quality, monitoring, and AI-ready data foundations. Build reliable pipelines integrating product, payment, and third-party data; establish data contracts, access controls, auditability, and semantic definitions; support real-time analytics and trustworthy reporting. Partner with Engineering, Data, and AI teams while maintaining infrastructure, incident response, documentation, and operational runbooks.

Build and own production data infrastructure for a healthcare AI platform. Responsibilities include REST API ingestion, Azure Event Hubs streaming into Databricks, Delta Lake medallion pipelines, entity resolution, semantic metrics, data-quality instrumentation, reconciliation, schema-drift handling, and troubleshooting source-to-warehouse discrepancies. The role requires strong Python and SQL skills, independent pipeline ownership, and experience with Databricks, Spark, PySpark, streaming, and healthcare-related data is a plus.

Own the Databricks enterprise data warehouse and BI solution, designing data models, ETL/ELT pipelines, stored procedures, semantic layers, and governed analytics. Lead healthcare data initiatives supporting value-based care metrics such as HCC, HEDIS, Stars, utilization, MLR, and capitation. Serve as BI product owner, manage roadmap and agile delivery, enforce data quality and HIPAA-aligned controls, and lead a small team while remaining hands-on.