Top Analysis Reporting Jobs in Wichita, KS

Leads the design and delivery of scalable analytics solutions using Azure Databricks, Power BI, and related platforms. Transforms and validates structured and unstructured data, applies statistical techniques, develops dashboards and analytical models, and implements data governance and quality processes. Partners with business and technology stakeholders to translate requirements into technical solutions, provides peer guidance, monitors data trends, and communicates actionable insights to technical and non-technical audiences.

Partners with live music venue operations and hospitality leaders to deliver business intelligence, dashboards, reporting, pricing strategies, guest insights, and cost-management analysis. Supports monthly and post-event reviews, data integrity, innovation, and operational excellence initiatives. Builds relationships with clients and stakeholders, experiments with process improvements, and serves as a subject-matter expert for live music programming.

Designs and maintains pipelines migrating financial data from legacy Oracle databases to Oracle ERP. Develops SQL and PL/SQL transformations, backend integrations, data mappings, reconciliation, testing, monitoring, troubleshooting, and documentation. Partners with accounting, business, and technical stakeholders to resolve issues and support large-scale financial transformation. The role also involves AI tool adoption, code reviews, solution design, deployment activities, governance, communication, mentoring, and project oversight.

Designs and maintains scalable data solutions on Palantir Foundry for FAA enterprise platforms. Responsibilities include modeling data with Palantir Ontology, developing data objects, actions, applications, workflows, pipelines, and AI integrations, while supporting governance, security, APIs, documentation, training, users, and stakeholders.

Leads data strategy and analytics for the Risk/Credit team, translating complex datasets into insights for Credit, Operations, Marketing, Product, and Finance. Responsibilities include automating Python/R workflows, building Tableau dashboards, partnering with Data Engineering on Databricks workflows, conducting strategic analyses, monitoring data quality, presenting recommendations to leadership, and documenting analytical methodologies. The role requires strong SQL, cloud data warehouse, visualization, analytics programming, distributed computing, and version-control expertise.

Lead data architecture consulting engagements, pursuit teams, client workshops, proofs of concept, and complex solution delivery. Design modern data architectures, integrate third-party platforms, create implementation roadmaps, and translate technical concepts for executive and technical audiences. Manage globally distributed teams, provide mentorship and thought leadership, support sales pursuits, and advise clients on data governance, quality, cataloging, lineage, master data management, cloud platforms, modernization, scalability, security, and AI-enabled solutions.

Lead the architecture and implementation of enterprise-scale GCP data ecosystems, including PB-scale platforms and AWS-to-GCP migrations. Establish data platform roadmaps, self-service architectures, governance, security, quality, and Infrastructure as Code standards. Architect solutions using GCP data, analytics, AI, streaming, and containerization technologies. Lead cross-functional engineering teams, mentor staff, advise executives, manage technical risks, and communicate the business value of data initiatives.

Own end-to-end data platform architecture across ingestion, lakehouse, warehouse, transformation, modeling, governance, and analytics delivery. Build pipelines, Spark and SQL transformations, data models, and production code. Design Databricks or Microsoft Fabric lakehouses, implement Delta Lake and medallion architecture, establish access controls and governance, and integrate databases, SaaS applications, APIs, files, and legacy systems. Evaluate platform choices based on client workloads, licensing, skills, and cost.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

Design, build, and support enterprise BI solutions including reports, dashboards, ETL/ELT, data marts, governed datasets and production support. Translate business requirements into technical designs, perform complex data analysis and root-cause investigations, document lineage and runbooks, optimize solutions, enforce data governance, and provide technical leadership or mentorship for large-scale initiatives.