Top Senior Analysis Reporting Jobs in Louisville, KY

Build and operate scalable cloud data pipelines, warehouses, transformation layers, and ML production systems. Lead data infrastructure architecture, warehouse performance optimization, DataOps monitoring, CI/CD improvements, data quality testing, and large-scale data product delivery. Collaborate across teams, promote data stewardship, and support batch and streaming pipelines while deploying, serving, and monitoring machine learning models.

Own the architecture and technical direction of Northbeam’s data ingestion and integration platform. Design scalable API-based ETL, event-driven and batch processing systems; establish standards for observability, freshness, and failure handling; and guide build-versus-buy decisions. Collaborate across engineering, infrastructure, product, and business teams while mentoring engineers, leading design reviews, and driving complex platform initiatives to completion.

Analyze performance marketing and subscription-funnel data, including acquisition efficiency, conversion, retention, churn, and customer lifetime value. Build automated Domo dashboards and governed reporting pipelines from multiple data sources. Investigate data anomalies, analyze A/B tests, define KPIs, and communicate insights to executives. Partner with marketing, product, engineering, finance, agencies, and BI contractors while independently executing analytics projects and improving reporting workflows.

Leads consumer and market insights for Yahoo Ads, partnering with sales and go-to-market teams to develop data-driven narratives, audience profiles, vertical trends, case studies, and client materials. Uses Yahoo first-party data, syndicated research, quantitative and qualitative methods, and generative AI tools to accelerate research. Builds validated analytical templates and self-service resources, collaborates on reporting pipelines and dashboards, and translates complex findings into executive-ready presentations.

Leads end-to-end data architecture, engineering pipelines, semantic-layer development, data quality, monitoring, and platform operations. Manages agile sprint planning, release delivery, DevOps metrics, and cross-functional project plans. Establishes MLOps and machine-learning platform capabilities, mentors data engineers, manages team members, and ensures reliable, well-governed data solutions for business intelligence and reporting.

Leads the design, optimization, and governance of scalable data architectures and pipelines. Ensures data quality, integrity, security, and compliance; mentors junior engineers; conducts audits and validation; and collaborates on data governance. The role requires expertise in SQL, Python, dimensional modeling, Snowflake on Azure, Azure Data Factory, Databricks, ETL, and data warehousing, with preferred experience in Airflow, Kafka, healthcare, data lineage, and slowly changing dimensions.

Designs and supports enterprise data integrations, ETL/ELT pipelines, APIs, data models, and transformations across Microsoft platforms. Maintains data quality, governance, security, and reliability while developing CI/CD pipelines, deployment automation, and release processes. Troubleshoots integration and deployment issues, manages environments, supports reporting and analytics, and collaborates with technical and business stakeholders to deliver scalable data solutions.

Build risk data models, analyze fraud and risk trends, create Tableau dashboards and automated reports, and deliver actionable insights to Risk Operations leaders. The role manages analytics requirements and roadmaps while using SQL, dbt, Dataform, and AI tools to support fraud strategy, compliance monitoring, loss forecasting, and executive reporting.

Leads Gartner research and thought leadership on data management, governance, and AI. Develops actionable insights, analyzes market trends, advises executive clients, delivers presentations, supports sales and conferences, reviews content, improves research processes, and mentors analysts. Requires deep expertise in data and analytics, AI implementation, data security, data value creation, executive communication, research, and strategic analysis. Remote U.S. role with travel up to 25%.

Build and maintain IICS ETL/ELT pipelines, develop Amazon Redshift data models, and use SQL and Python for data transformation and automation. Create Power BI reporting models, implement data quality checks, document pipelines, and collaborate with client stakeholders and engineering teams. The role requires autonomous work, strong communication, and the ability to translate technical solutions into business context, with bonus value for Veeva or life sciences experience.