Top Analysis Reporting Jobs in Kansas City, MO

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).

Leads LTK’s Data Engineering team, owning technical direction, architecture, pipelines, data products, governance, quality, reliability, and platform modernization. Manages and develops engineers, drives roadmaps and complex initiatives, partners with cross-functional stakeholders, and balances scalability, security, performance, cost, and business priorities. Establishes engineering standards, improves operational practices, manages risks and dependencies, and builds trusted, reusable data capabilities supporting analytics, reporting, products, and AI use cases.

Lead Workday reporting strategy for higher education: design Advanced, Matrix, Composite, and Dashboard reports; implement row-level security and role-based access; partner with HR/Finance/Payroll/Institutional Research; support regulatory and executive reporting; manage testing, validation, and user training while ensuring governance and data standards.

Support Items Master Data Management by collecting, cleansing, and analyzing supply chain product, contract, and pricing data. Build SQL-based reports and dashboards, ensure data quality and governance, support system implementations and migrations, and collaborate cross-functionally to drive standardization and operational improvements.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

Designs and stewards enterprise ETL/ELT pipelines, lakehouse, warehouse, and data models using Microsoft Fabric, SQL, and Python. Establishes data quality, testing, lineage, security, governance, DataOps, CI/CD, and performance optimization practices. Uses AI coding and agentic tools for development while reviewing outputs rigorously. Partners with stakeholders to shape requirements, leads complex initiatives, mentors engineers, and collaborates with analysts, data scientists, and BI teams to deliver reliable data products.

Leads actuarial financial data systems and marts, developing data solutions, extracts, reports, analyses, automations, validations, and executive reporting support. Manages data mart maintenance, audits, business requirements, technical specifications, user acceptance testing, and system implementations. Provides technical leadership, coordinates vendors and departments, trains junior staff, and advises project teams on data architecture, business rules, configuration, and financial data quality.

Supports enterprise database consolidation, migration, and system integration initiatives. Analyzes source and target databases, business processes, data relationships, and dependencies; develops source-to-target mappings; defines transformations and cleansing rules; investigates discrepancies; supports testing, audits, reconciliation, documentation, and post-conversion stabilization. Collaborates with business and technical stakeholders to resolve data-quality issues and improve migration processes.

Supports information collection and organization for manuals, training materials, installation guides, proposals, and reports. Edits technical and customer-facing documentation, assists with financial and administrative tasks, and maintains systems, operations, and procedural documentation libraries. Collaborates remotely with project managers, requirements analysts, Scrum Masters, developers, testers, and government stakeholders in Agile ceremonies while complying with CUI and cybersecurity requirements.

Serves as the liaison between Data Operations and business teams by intake, triaging, and analyzing file and data issues. Maintains issue dashboards, tracks resolution status, communicates proactively with stakeholders, documents analyses and resolutions, and identifies recurring problems for process improvement. The role requires translating technical findings for non-technical audiences and managing multiple issues across client management, patient care, and technical teams.