Top Analysis Reporting Jobs in Rochester, NY

Own the Finance and Operations data layer, integrating systems into Snowflake and Omni, building reusable data models, dashboards, governed metrics, validation checks, and reconciliation workflows. Partner with Finance, Operations, and Data teams to translate business processes into trusted analytics, improve data quality, automate reporting, and support leadership decision-making.

Analyzes healthcare claims, provider, pharmacy, and enrollment data to identify trends, improve data quality, optimize workflows, reduce costs, and support business decisions. Translates business needs into requirements, develops complex SQL queries, validates data, recommends process improvements, coordinates projects, and serves as a liaison among operations, research and development, IT, and external partners. Also mentors team members and communicates technical findings to nontechnical stakeholders.

Owns and codifies business definitions and calculation methods for legal spend analytics, audits legacy Excel/PowerPoint artifacts, validates analyses (SQL and AI), supports reporting and storytelling for senior law department and C-suite audiences, and helps migrate analyses into modern analytics tooling.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Develops and manages enterprise business intelligence products, including semantic models, governed definitions, metadata, dashboards, and AI-assisted analytics capabilities. Translates complex business needs into measurable analytic solutions, advises stakeholders, supports adoption and training, and manages product lifecycle, quality, performance, and business impact. Partners with product managers and business leaders to prioritize work, manage risks, communicate value, and guide less experienced team members.

Analyze web, journey, survey, and marketing data to uncover actionable insights for enterprise clients. Translate technical findings into business recommendations, test-and-learn plans, dashboards, reports, and presentations. Collaborate with account teams, ensure data quality and statistical rigor, investigate anomalies, and support client questions. The role requires expertise in analytics platforms, data visualization, spreadsheets, SEO, and client-facing data storytelling in a fast-paced SaaS environment.

Leads enterprise analytical modeling and semantic architecture, establishes standards for testing, documentation, governance, lineage, observability, and access, and develops reusable governed data products. Partners across Product, Engineering, Finance, Clinical, Research, Marketing, and AI teams; guides architecture reviews, data quality ownership, semantic layer design, and governance adoption. Mentors engineers and drives modernization of analytical environments.

Leads Versapay’s enterprise data strategy, architecture, governance, quality, accessibility, and commercialization. The role unifies transactional and analytical data, establishes semantic models and data catalogs, enables secure AI and agentic capabilities, develops external data products, manages data platform costs, and leads teams across data engineering, analytics, BI, and platform operations. The Senior Director partners with executive, product, engineering, commercial, finance, legal, and compliance stakeholders.

Supports Indonesian and broader Asian survey operations by monitoring data quality, managing quality-control staff, correcting survey issues, analyzing collection progress, and developing data-quality tools. Coordinates field operations, training, stakeholder engagement, translations, and backcheck processes. Provides insights on coffee and cacao sustainability data to country teams and supply-chain stakeholders. The role is fully remote from Indonesia with travel to regional agricultural areas.

Supports the design and development of scalable end-to-end data pipelines and cloud data platforms. Responsibilities include improving data reliability and quality, implementing data management practices, supporting automation and process improvements, ensuring secure and cost-effective solutions, and recommending system enhancements. The intern collaborates with global teams and gains hands-on experience in data engineering, project coordination, and innovation management.