Top Senior Analysis Reporting Jobs in Louisville, KY

Design and implement enterprise data architectures supporting batch and real-time analytics, streaming pipelines, data warehouses, lakehouses, and generative AI applications. Build hands-on ETL/ELT solutions using Python and SQL, with Treasure Data/CDP, Kafka, Snowflake, Databricks, cloud services, CDC, and Debezium. Develop AI-ready pipelines, semantic search, RAG and vector-search infrastructure, and integrate enterprise data with modern AI platforms. This remote contract requires production-grade architecture experience rather than traditional ETL or BI maintenance alone.

Conduct market research and competitive analysis, develop financial models, identify market trends, and provide strategic recommendations to senior leadership. The role supports sales projections, pricing, product positioning, marketing campaigns, and growth strategy. Responsibilities include monitoring market drivers, preparing trend updates, engaging external research firms, and attending industry events. The position requires strong quantitative, financial, communication, problem-solving, and cross-functional collaboration skills.

Analyze clinical data completeness, reliability, and effectiveness across healthcare facilities, vendors, interoperability networks, and integration pathways. Reconcile claims with clinical records, identify missingness and latency, report ADT coverage, evaluate data technologies, recommend vendor configurations, and prioritize facilities for direct acquisition. Partner with product, engineering, and clinical teams to improve scalable, trustworthy data pipelines and support TEFCA and QHIN strategy.

Leads the Sales Analytics and Reporting function and manages Sales Analysts. Oversees dashboards, scorecards, KPI tracking, profitability analysis, business insights, executive reporting, and sales technology platforms. Partners with Sales, Finance, Product, Technology, and other stakeholders to improve performance, profitability, planning, and decision-making. Develops team capability, reporting processes, platform adoption, and analytical effectiveness while translating complex data into actionable recommendations.

Manage human capital analytics and workforce metrics, including hiring-process analysis, time-in-stage, time-to-hire, yield rates, benchmarking, trend analysis, and performance measurement. Develop dashboards, visualizations, executive briefings, analytical presentations, and reports using business intelligence tools. Communicate complex findings and actionable recommendations to senior leadership while supporting federal or large organizational clients.

Leads customer data engineering strategy, delivery, team development, and roadmapping. Oversees data-driven product improvements, digital programs, quality initiatives, budgets, cybersecurity remediation, and portfolio management. Manages, mentors, and grows data engineering teams, including contractor teams, while guiding customer data platforms, omnichannel identity resolution, complex data modeling, and personalization-focused data science capabilities. Partners across the organization to execute strategic initiatives and build team capability.

Designs, builds, tests, deploys, and maintains secure ETL/ELT pipelines for public health data. Integrates Power Platform, Azure services, APIs, SQL Server, CDC/NIOSH systems, and approved file-transfer platforms. Develops batch, event-driven, and near-real-time data workflows supporting intake, validation, reporting, analytics, notifications, and results delivery while meeting FISMA Moderate, federal privacy, Agile, and DevSecOps requirements.

Designs, develops, and maintains Databricks-based ETL pipelines, data integration solutions, data warehouses, and reporting datasets. Builds batch and streaming architectures using Python, Spark, SQL, and Delta Lake; optimizes performance and costs; migrates legacy SSIS and SQL Server processes; maintains SSRS reports; implements data quality controls; and collaborates with business and technical teams supporting analytics and AI/ML workloads.

Lead complex customer analytics engagements, translating industrial business needs into scalable analytics architectures and solutions. Advise customers, drive product adoption, identify high-value use cases, mentor Analytics Engineers, resolve technical escalations, and influence product roadmaps. Apply expertise in industrial process data and sectors such as power, pharmaceuticals, and semiconductors. Collaborate with customers, partners, product teams, and account teams to deliver measurable business outcomes.

Leads and develops the Data Engineering team while remaining hands-on with scalable pipelines, ETL/ELT processes, data warehouses, integrations, and infrastructure. Establishes architecture, reliability, quality, and performance standards; guides technical strategy; improves automation and monitoring; and partners with Finance and business stakeholders to translate data needs into practical solutions.