Top Senior Data & Analytics Jobs in Rochester, NY

Design, develop, maintain, and optimize enterprise ETL pipelines supporting Army Human Resources Command data. Build data mappings and transformation logic, ensure data quality and security compliance, maintain database systems, manage scheduling and monitoring for reliable pipelines, provide lifecycle technical solutions, and create architecture and data-flow documentation using DataStage and SQL databases.

Leads the enterprise data function, including strategy, platform modernization, analytics, data science, governance, architecture, and talent development. Oversees migration from Crystal Reports and Oracle to Databricks and Power BI, builds data connectivity and quality practices, establishes a data science function, develops internal expertise, and advises senior leadership on data-driven decisions.

Leads enterprise analytics strategy, data integration, governance, reporting, dashboards, forecasting, and advanced business analysis. Manages analysts and partners with Sales, Pricing, Finance, Product Management, Operations, and executive leadership to translate complex data into actionable recommendations. Oversees Power BI dashboards, KPI frameworks, data quality, predictive modeling, and reporting automation to improve growth, profitability, pricing, and operational performance.

The Senior Pharmacy Business Analyst monitors pharmacy performance, identifies trends and root causes, and translates operational and financial data into actionable recommendations. The role builds Tableau dashboards, queries enterprise data warehouses with SQL, prepares executive reporting, and partners with pharmacy, Finance, Operations, and Clinical leaders. Responsibilities include recurring report ownership, quality assurance, planning support, ad hoc analysis, and communicating insights to senior stakeholders.

Leads data engineering strategy and mentors an analytics engineering team. Designs scalable ELT pipelines, warehouse integrations, data models, API ingestion workflows, and data quality frameworks using cloud and database technologies. Conducts exploratory analysis, supports dashboards and analytical solutions, monitors warehouse performance and costs, and ensures data governance, security, and compliance. Collaborates with data scientists, analysts, engineers, and business stakeholders to deliver healthcare analytics solutions.

Leads the architecture, implementation, and evolution of enterprise data platforms, including Master Data Management, data lakes, lakehouses, and cloud data services. Manages data engineers and developers, establishes engineering standards, oversees Azure-based integrations and pipelines, and owns data applications, databases, security, governance, and production support. The role also directs technical strategy, manages multiple initiatives, and communicates architecture and delivery plans to stakeholders.

Leads qualitative and quantitative market research to uncover customer, market, competitive, and healthcare insights. Designs and manages studies, analyzes data using statistical and AI-assisted tools, develops reports and dashboards, presents recommendations, maintains research quality, and coordinates external partners. Collaborates with product, engineering, sales, marketing, and customer success teams to influence product strategy, growth, innovation, and customer experience initiatives.

Lead the data engineering strategy and architecture for distributed pharmaceutical data systems. Design and scale pipelines, APIs, and data platforms while ensuring reliability, governance, quality, and PII/PHI protection. Drive technical decisions, improve developer efficiency, deliver business impact, influence cross-functional roadmaps, mentor engineers, communicate with executives, and promote organizational adoption of new technologies and processes.

Design and own a unified data model for an AI-driven pipeline risk platform. Responsibilities include lakehouse and medallion architecture, geospatial modeling, entity resolution, ingestion patterns, governance, lineage, data quality, access controls, and traceability. Partner with data engineers, application engineers, and data scientists to implement schemas, pipelines, serving layers, and optimization strategies while maintaining clear architecture documentation.

Build and operate reliable ETL and ELT pipelines across lakehouse and transactional systems. Develop data models, enforce governance, integrate diverse data sources, and support analytics, APIs, and predictive tools. Monitor performance, data quality, lineage, cost, and uptime while collaborating with data science, AI, product, and innovation teams.