Top Senior Analysis Reporting Jobs in Louisville, KY

Own and improve vehicle application and product catalog data across PIM systems. Collaborate with Category, Operations, Suppliers, UX, Product, and Engineering to define data standards, implement governance, run audits, train suppliers, deliver analytics and KPIs, and drive roadmap and tooling to improve data quality and customer experience.

Design, develop, and maintain dashboards, semantic models, and reports using Microsoft Fabric, Power BI, and Snowflake. Analyze high-volume data sets, write and optimize complex SQL (PostgreSQL), ensure data quality, collaborate with cross-functional stakeholders, and support report migrations and deployments. Provide actionable insights to drive business decisions and work independently on complex analytics projects.

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.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Design and build petabyte-scale multimodal data pipelines and infrastructure (text, audio, images, video). Own and maintain systems like Spark, Ray, and vector databases, partner with pre/post-training teams to improve data recipes through experimentation, and support large-scale dataset storage and processing for AI model training.

Build and operate batch and near-real-time data pipelines, semantic models, certified measures, APIs, and serving infrastructure for AI-powered decision systems. Responsibilities include data quality, observability, lineage, governance, CI/CD, infrastructure as code, performance optimization, model scoring pipelines, and AI telemetry. Partner with data scientists and business stakeholders to productionize models and deliver reusable, documented data platform capabilities.

Lead a small analytics team (staff data scientist + two analysts) to deliver curriculum, product, and program insights. Split time between people management (60-70%) and hands-on analysis (30-40%), advance experimentation and measurement, build AI/LLM-driven agentic workflows, manage sprints and cross-functional stakeholder relationships, and drive analytics that inform curriculum, product, and intervention strategies.

Design and build PerfectServe’s unified cloud data platform, including ingestion pipelines, integrations, data models, metrics, and consumer-facing data layers. Establish architecture, engineering, quality, and testing standards; enable safe extraction from production systems; partner with data users; and mentor data engineers. The role requires substantial cloud data platform experience, deep SQL, warehouse expertise, ELT, change-data-capture, AWS, modeling, orchestration, and data quality skills.

Designs, builds, and maintains enterprise data pipelines, ETL processes, integrations, data infrastructure, and complex data models. The role supports analytics partners, develops scalable data warehouse solutions, tunes SQL and databases, troubleshoots production issues, and collaborates with architects, analysts, developers, and stakeholders. Responsibilities include end-to-end project delivery, data modeling, big data engineering, production support, agile planning, and mentoring team members.

Designs, builds, and maintains enterprise data pipelines, ETL processes, integrations, cloud data infrastructure, and complex data models. Supports analytics partners, develops data warehouse solutions, tunes SQL and database performance, troubleshoots production issues, and delivers end-to-end data engineering projects. The role collaborates with architects, analysts, developers, and business stakeholders, applies big data technologies, supports agile delivery, and mentors team members.

This role involves writing user stories, supporting agile team processes, and driving customer discovery to enhance technology solutions for clients.

Leads scalable data model and pipeline design, dbt development, testing, CI/CD, and analytics engineering implementations. Partners with analysts, engineers, and stakeholders to translate business needs into reliable models and semantic layers. Advises on data architecture, governance, quality, performance, and long-term scalability while mentoring peers and contributing to shared tooling, standards, and frameworks.

Develops and supports data architecture and medical imaging informatics solutions on the XNAT platform. Responsibilities include data integration, modeling, storage and delivery optimization, data-sharing, coding, testing, release management, defect reduction, technical documentation, and partner support. The role collaborates with research and clinical teams, oversees stable XNAT releases, and advances platform capabilities. Required qualifications include a bachelor’s degree or equivalent experience, five years of data-related experience, and PostgreSQL skills.