Top Analysis Reporting Jobs in Wichita, KS

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

As a Salesforce Technical Architect focused on Data & AI, you'll design and implement solutions using Salesforce Data 360, oversee technical projects, collaborate with various stakeholders, and mentor junior staff to drive AI innovations.

Trace3 seeks enthusiastic individuals for its Data Intelligence Team. The role focuses on innovative technology solutions and consulting services, fostering a collaborative and dynamic work environment.

Perform part-time quality audits and evaluations of task outputs, define and refine quality benchmarks and scoring rubrics, analyze audit results to produce actionable insights and reports, and recommend process improvements to raise output quality.

Develop and lead healthcare analytics and BI solutions for HIS products: design, code, and deliver enterprise-scale applications and dashboards, work with AWS data services and BI tools, support product development and troubleshoot reporting issues for global customers.

Lead Data Engineer responsible for defining architecture, engineering standards, and best practices for the enterprise data platform, collaborating with distributed teams for modernization and scalability.

Assist in collecting, cleansing, and analyzing datasets to produce actionable insights, reports, and dashboards for informed business decisions.

Designs and delivers a global analytics platform supporting reporting, visualizations, self-service analytics, and embedded data products. Responsibilities include data collection and processing, semantic modeling, warehouse and pipeline development, query optimization, governance, analytics enablement, and stakeholder collaboration. The role provides actionable insights from complex travel data and builds integrated analytics applications using cloud platforms and business intelligence tools.

Design, build, maintain, and optimize Spark and Scala ETL/ELT pipelines on AWS for terabyte- and petabyte-scale datasets. Work across S3, Snowflake, Kafka, and monitoring systems, resolve production data-quality and performance issues, write automated tests, participate in architecture and code reviews, and support on-call operations. Use generative AI to improve pipeline development, monitoring, and engineering productivity.

Design and architect robust ETL/data pipelines on cloud platforms. Build and automate data ingestion and preprocessing using Spark/Databricks, AWS Glue, Airflow. Implement warehousing architectures (EDW, DM, ODS, MOLAP/ROLAP), ensure SQL-based data quality, use version control, and deliver tested production pipelines while communicating with stakeholders.