Top Senior Analysis Reporting Jobs in Buffalo, NY

Designs, develops, and maintains scalable distributed data pipelines and ETL workflows. Ensures data quality, integrity, security, privacy, and availability; optimizes data processing performance; monitors production systems; diagnoses root causes; documents architectures and procedures; and provides rotational on-call support for critical data systems.

Leads advanced analytics, business intelligence, reporting automation, dashboards, forecasting, data governance, and performance insights. Partners with executives, clients, data engineering teams, and stakeholders to translate complex data into strategic recommendations, improve business performance, and support decision-making. Oversees analytical projects, reporting standardization, data quality, technology improvements, and analyst mentoring.

Analyzes complex data, develops and maintains reports and dashboards, defines product metrics and KPIs, documents reporting processes, and translates findings into actionable insights for technical and non-technical stakeholders. Partners with cross-functional teams, recommends reporting improvements, ensures data supports business needs, and may coach other analysts.

Designs and maintains scalable cloud data architectures, pipelines, ETL processes, data warehouses, databases, and data models. Ensures data quality, accuracy, security, availability, and consistency across sources. Develops SQL queries for analytics and reporting, and documents pipelines, schemas, architectures, and models. The role requires expertise with Python, Java, Scala, R, SQL, relational and NoSQL databases, cloud platforms, and Snowflake.

Leads data discovery, profiling, quality assessment, and Source-to-Target Mapping for wealth management data platforms. Analyzes complex financial datasets using advanced SQL, documents business rules and transformations, translates requirements for ETL and data engineering teams, supports data governance and testing, and communicates findings to technical and business stakeholders.

Leads the design and delivery of scalable analytics solutions using Azure Databricks, Power BI, and related platforms. Transforms and validates structured and unstructured data, applies statistical techniques, develops dashboards and analytical models, and implements data governance and quality processes. Partners with business and technology stakeholders to translate requirements into technical solutions, provides peer guidance, monitors data trends, and communicates actionable insights to technical and non-technical audiences.

Designs and maintains pipelines migrating financial data from legacy Oracle databases to Oracle ERP. Develops SQL and PL/SQL transformations, backend integrations, data mappings, reconciliation, testing, monitoring, troubleshooting, and documentation. Partners with accounting, business, and technical stakeholders to resolve issues and support large-scale financial transformation. The role also involves AI tool adoption, code reviews, solution design, deployment activities, governance, communication, mentoring, and project oversight.

Designs and maintains scalable data solutions on Palantir Foundry for FAA enterprise platforms. Responsibilities include modeling data with Palantir Ontology, developing data objects, actions, applications, workflows, pipelines, and AI integrations, while supporting governance, security, APIs, documentation, training, users, and stakeholders.

Leads data strategy and analytics for the Risk/Credit team, translating complex datasets into insights for Credit, Operations, Marketing, Product, and Finance. Responsibilities include automating Python/R workflows, building Tableau dashboards, partnering with Data Engineering on Databricks workflows, conducting strategic analyses, monitoring data quality, presenting recommendations to leadership, and documenting analytical methodologies. The role requires strong SQL, cloud data warehouse, visualization, analytics programming, distributed computing, and version-control expertise.

Own end-to-end data platform architecture across ingestion, lakehouse, warehouse, transformation, modeling, governance, and analytics delivery. Build pipelines, Spark and SQL transformations, data models, and production code. Design Databricks or Microsoft Fabric lakehouses, implement Delta Lake and medallion architecture, establish access controls and governance, and integrate databases, SaaS applications, APIs, files, and legacy systems. Evaluate platform choices based on client workloads, licensing, skills, and cost.