Top Remote Analysis Reporting Jobs in Louisville, KY

Designs and builds modern data applications, pipelines, transformations, enrichment processes, provisioning layers, and interfaces supporting clinical and operational healthcare processes. Analyzes clinical data to identify trends, collaborates with Product, Platform, and Architecture teams, mentors junior data engineers, and evaluates emerging technologies. The role emphasizes cloud computing, big data, data science, modern development frameworks, source control, documentation, and repeatable engineering practices.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

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.

Leads advanced analytics initiatives supporting sales, marketing, and operations strategy. Develops statistical and predictive models, dashboards, KPI reporting, and customer analyses using large datasets. Partners with stakeholders and data engineering teams to translate business questions into actionable insights, communicates findings to executives, and mentors junior analysts.

Lead analytical support for performance marketing by evaluating CAC, ROAS, LTV, conversion, retention, and acquisition efficiency. Conduct deep-dive analyses, experimentation, incrementality studies, and marketing measurement using SQL, Python, and visualization tools. Build scalable reporting frameworks, improve data quality, communicate insights to senior stakeholders, influence channel and budget decisions, and mentor junior analysts.

Architects FHIR-compliant clinical data models and develops harmonization, enrichment, and validation strategies across EHR, HIE, and claims data. Maintains clinical ontologies and value sets, ensures data accuracy and longitudinal integrity, and documents technical requirements for engineering teams and stakeholders. The role requires advanced Python and SQL skills, healthcare interoperability expertise, and experience with clinical informatics or data integration.

Build and optimize scalable Databricks data pipelines across a medallion architecture. Develop data models, implement data quality checks and validation, integrate Azure services, and ensure data accuracy, governance, lineage, security, and performance. The role requires designing config-driven pipelines supporting CDC and event-based processing, maintaining CI/CD deployments, and working with structured and unstructured data across SQL and NoSQL systems.

Lead the architecture and delivery of modern data and analytics platforms for clients. Design governed, secure solutions using Microsoft Fabric, Azure, Databricks, Power BI, and Purview. Translate business needs into scalable architectures, estimates, roadmaps, and delivery plans. Guide architecture reviews, governance, CI/CD, testing, monitoring, and operational readiness while enabling AI, Copilot, RAG, and intelligent application initiatives. Serve as the technical lead and trusted advisor for client engagements.

Defines and documents client business and technical requirements for analytics solutions, collaborates with developers on design and testing, and delivers data ingestion, reporting, dashboards, business intelligence, data warehousing, and advanced AI/ML applications. Partners with delivery and account management teams to ensure customer satisfaction, provide analytics consulting, and recommend appropriate cloud and BI technologies.

Leads business analysis, advanced analytics, KPI development, data modeling, reporting automation, and AI/ML initiatives supporting global data-center construction and operational excellence. Builds datasets, dashboards, performance metrics, forecasts, and scenario models; translates complex findings for executives; aligns technology solutions with business needs; and promotes data governance, documentation, process improvement, and analytics maturity across cross-functional teams.