Top Senior Analysis Reporting Jobs in Buffalo, NY

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.

Oversee data ingestion and transformation, manage finance data sources, ensure scalability and reliability of data platforms, and collaborate with stakeholders to align data engineering with organizational goals.

The Senior Reporting & Analytics Consultant leads customer-focused reporting and analytics engagements, developing solutions, supporting implementations, and training clients, while ensuring project success.

As a Senior Data Engineer, you will design and maintain scalable data models, build production data pipelines, and support analytics across various business functions.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

The Director, Research - Power Markets is responsible for leading the QA/QC process for long-term forecasting, advising leadership, and ensuring market insights are effectively integrated into forecasts.

Design, build, and optimize Snowflake-based data platform: develop ELT pipelines, data models, governance, security, performance tuning, cost optimization, CI/CD, and advanced Snowflake features. Collaborate with stakeholders, mentor engineers, and deliver scalable data solutions for analytics.

The Staff Analytics Engineer will own the Financial Subledger Data Platform, build dbt models, implement data quality controls, and mentor a junior engineer, ensuring high operational reliability and cross-functional collaboration.

Design and build data warehouse architecture, develop ETL/ELT pipelines, implement data governance, and partner with teams to improve data systems.