Top Senior Data & Analytics Jobs in Buffalo, NY

The Data Analyst in Revenue Operations will analyze sales data, build models, and create reports using SQL, Excel, and BI tools to empower business decisions.

Design, build, and operate end-to-end data pipelines and curated compliance datasets powering transaction monitoring, KYC/EDD, and screening. Ensure data quality, lineage, and audit readiness; partner with Compliance and Engineering to improve detection signal quality, define metrics, and deliver repeatable reporting and measurement frameworks for control effectiveness.

Analyze data processes, partner with teams to modernize data architecture, and support data migration. Document and oversee functional specifications, ensuring compliance and optimizing database structures.

Lead development of BI solutions, dashboards, and automated financial reports to ensure data integrity and drive actionable insights. Partner with IT and finance teams to improve data collection, optimize analytics processes, and support business strategy and performance monitoring across a large, matrixed organization.

Lead reporting and analytics for BSA/AML/OFAC and fraud investigations: source, analyze, and visualize complex data; deliver regulatory reports; automate reporting; manage data pipelines; mentor teammates; and collaborate with stakeholders to drive data quality and analytics strategy.

Lead EHS data strategy by designing, building, and maintaining scalable data pipelines, models, and governance. Integrate multi-source EHS data into centralized platforms, implement quality checks, develop Power BI dashboards, produce analytics and predictive insights, and collaborate with IT to support cloud data architecture and automation to improve EHS reporting and risk management.

Design and implement Informatica ETL solutions (PowerCenter) and Data Quality processes; develop mappings and workflows; deploy on Unix, Teradata, SQL Server, and Oracle; perform performance tuning and optimization; collaborate with business users and team members.

Analyze large complex datasets to identify trends and anomalies, produce actionable insights and financial models, document processes, present findings to stakeholders, manage projects and client relationships, mentor junior staff, and support planning and delivery.

Design, build, and maintain scalable data models and pipelines using Python and SQL. Collaborate with product and SMEs to create analytics-ready healthcare datasets, maintain data engineering systems, document solutions, and iterate based on product feedback.

Lead healthcare data analysis and quality efforts across claims, pharmacy, and enrollment data. Translate business needs into technical requirements, build complex queries, recommend process and data improvements, manage projects, and mentor team members while liaising between operations, R&D, and IT.