Top Analysis Reporting Jobs in Wichita, KS

Leads and manages an analytics engineering team while contributing to data transformation, modeling, quality, and delivery solutions. Establishes modeling and development standards, implements analytics engineering tools, supports client engagements, improves reporting and visualization processes, allocates team resources, mentors engineers, supports presales, and drives internal quality and process improvements.

Analyzes business and operational needs, gathers requirements, evaluates data and systems, and recommends technology solutions. Develops advanced SQL queries, reports, system models, and process improvements. Responsibilities include troubleshooting, data architecture integration, software and hardware solution design, database analysis, automation using scheduling or RPA tools, and project leadership. Senior levels guide other analysts and assess technology’s business impact.

Design and implement enterprise data architectures supporting batch and real-time analytics, ETL/ELT, data warehouses, streaming pipelines, CDC, and cloud data platforms. Build AI-ready data infrastructure for RAG, vector search, and Generative AI applications. The role requires production experience with Treasure Data/CDP, Kafka, Snowflake or Databricks, cloud services, and modern AI data engineering technologies.

Manages the customer care call quality monitoring program across multiple teams. Maintains quality standards, scoring configurations, dashboards, and reporting; analyzes contact trends and customer insights; partners with managers to improve coaching and performance; administers the quality management platform; develops training and support materials; and collaborates with customer experience and technology teams to improve customer interactions.

Owns analytical projects across customer onboarding, transaction behavior, and platform operations. Designs dashboards, KPI frameworks, reporting workflows, and data pipelines while delivering actionable insights. Partners with Engineering, Product, Payment Operations, Compliance, and Finance; mentors colleagues; manages project scope and priorities; resolves ambiguity; and drives cross-functional alignment. Requires advanced SQL and data modeling skills, BI tool experience, analytical scripting familiarity, FinTech domain knowledge, and 4+ years of analytics experience.

Lead analytics partner to Community Support, driving data-driven roadmaps, scalable reporting and measurement, causal inference and experimentation, and improvements to agent/guest/host experiences via analytics, modeling, and stakeholder influence.

Delivers financial and operational reporting, dashboards, forecasting, variance analysis, and profitability insights for Financial Services clients. Uses SQL, Power BI, and Excel to validate data, identify anomalies, support client implementations, and improve reporting processes. Partners cross-functionally with accounting, operations, analytics, FP&A, vendors, and leadership while maintaining data governance, documentation, and reporting standards.

Build and maintain production data pipelines that transform robot logs and telemetry into reliable, queryable datasets. Design Spark-based ETL workflows, orchestrate processing with Airflow or similar tools, manage gold-layer datasets, and implement data quality, schema evolution, monitoring, and metadata practices. Collaborate with robotics, hardware, reliability, analytics, and ML teams on data modeling, fleet insights, debugging, and root-cause analysis. The role may also contribute to Python, Java, or C++ libraries supporting data capture and consumption.

Builds and maintains Power BI reports, semantic models, Power Automate workflows, and Microsoft 365 solutions for Legal, Governance, and HR. Gathers requirements, maps processes, performs data governance audits, improves data quality, evaluates AI and Copilot use cases, and supports solution documentation, training, adoption, and technical guidance for a working student.

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.