Top Analysis Reporting Jobs in Buffalo, NY

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.

Own and evolve the analytics platform, including data models, pipelines, metric definitions, semantic layers, dashboards, and self-service data products. Partner with cross-functional stakeholders to translate business needs into reliable technical solutions. Lead data initiatives, improve ELT reliability and governance, resolve quality issues, mentor teammates, and shape the Analytics team’s technical roadmap. The role requires strong SQL, dbt, modern data-stack experience, business communication, and independent execution in an ambiguous environment.

Own analytics, modeling, reporting, and recommendations for portfolio management. Design underwriting and pricing for multicard and line-extension strategies, test rewards upgrades and purchase incentives to boost engagement, and partner with risk, data science, and engineering to operationalize strategies and defend recommendations to stakeholders.

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.

Build and maintain a global knowledge base of electronic-resource metadata. Responsibilities include analyzing publisher data, creating and maintaining collections, establishing data feeds, researching missing metadata, documenting transformation processes, resolving data issues through root-cause analysis, coordinating with vendors, and managing workload priorities. The role requires advanced Excel skills, attention to data quality, strong communication, and familiarity with metadata standards.

The Principal Data Engineer designs and builds scalable cloud-native data platforms, pipelines, frameworks, and governed data products supporting analytics, reporting, AI, and operational workloads. Responsibilities include Databricks, Spark, Delta Lake, Azure, SQL Server, batch and streaming processing, data integration, performance optimization, governance, modernization, troubleshooting, architecture reviews, and mentorship. The role provides senior technical leadership without direct people management and supports insurance-domain data across policy, claims, billing, finance, and regulatory functions.

Leads enterprise data architecture strategy, modernization, and multi-year platform roadmaps. Defines standards for data models, ingestion, transformation, orchestration, quality, governance, observability, and consumption across batch and streaming environments. Provides technical leadership to data engineering and analytics teams, oversees scalable data solutions, mentors technical leaders, and partners with business, engineering, security, and data science stakeholders. Evaluates technologies, guides vendor selection, enables data products, and explores GenAI applications.