Top Senior Analysis Reporting Jobs in Louisville, KY

Senior AWS Analytics Engineer. Posting contains no detailed responsibilities or qualifications beyond the job title.

Lead design and build of Microsoft Fabric data solutions and Power BI semantic models. Migrate Tableau reports to governed Power BI, develop Spark notebooks, implement medallion lakehouse patterns, optimize ETL/ELT and DAX, and support CI/CD and stakeholder validation.

Lead development and maintenance of actuarial data marts, extracts, reports, validations and audits. Drive requirements, technical specs, automations, and financial analyses; mentor staff and coordinate with vendors and business partners to ensure accurate, auditable financial data.

Design and implement scalable data pipelines and orchestration on GCP to support AI/ML-driven mail intelligence. Build stream and batch processing, ensure data governance and quality, optimize workflows, create visualizations, and collaborate with US cross-functional teams to align technical strategy and recover from failures.

Design, develop, and maintain Snowflake-backed semantic models and Power BI reports; build SQL queries, functions, and stored procedures; use AI-assisted tooling (Claude, MCP) to accelerate BI development; manage work in Azure DevOps, version control with GitHub; ensure QA, documentation, stakeholder communication, and mentor fellow developers.

Design, develop, and optimize ETL workflows, data platforms, and reporting solutions. Lead technical designs, troubleshoot production issues (including off-hours support), collaborate with stakeholders and vendors, document processes, and drive automation and BI/dashboard implementations to ensure scalability, performance, and reliability.

Lead reporting and analysis across product, call center, and marketing; manage enrollment and revenue reconciliation; produce partner and carrier reports; analyze member engagement and plan performance to surface actionable insights.

Design, build, and maintain end-to-end batch and streaming data pipelines on GCP. Migrate legacy warehouses to BigQuery/Bigtable/ClickHouse, orchestrate workflows in Airflow, ensure data quality and observability, and partner with ML engineers on feature pipelines, drift monitoring, and retraining.

Design and implement scalable, fault-tolerant big-data and cloud-based data applications to support low-latency fraud analytics. Partner with architects, data scientists and product teams to build pipelines, integrate AI services, ensure data management standards, and drive production deployments and automation in a scaled Agile environment.

Lead complex analytical initiatives, build executive dashboards and KPI frameworks, perform advanced SQL analysis, forecasting and root-cause analysis, partner with senior stakeholders, improve data governance and BI solutions, and mentor junior analysts to drive operational performance and cost/resource optimization.