Top Senior Data & Analytics Jobs in Buffalo, NY

The Data Engineer builds and maintains data infrastructure, develops data pipelines, ensures data quality, and collaborates with teams for insights.

As a Senior Data Engineer, you will design and maintain scalable data pipelines, focusing on architecture, ingestion, storage, and analytics on GCP. You'll collaborate with stakeholders and optimize data structures for performance while ensuring adherence to data governance and compliance standards.

Design, build, and own end-to-end data systems and pipelines powering payments, fraud response, and reporting. Implement streaming and batch integrations, APIs, and workflow orchestration. Define data correctness with monitoring, alerting, and tests. Create reusable patterns and collaborate with stakeholders to clarify requirements and tradeoffs.

The Staff Risk Analytics role involves overseeing fraud risk management, developing strategies, leading cross-functional initiatives, and providing real-time analytics in fintech.

The Head of Data at BetterSleep will own the data function, manage a team, develop data infrastructure, and enhance analytics and measurement strategies to support product and growth initiatives.

The Senior Data Scientist will lead analytics efforts, develop data models, and improve data pipelines to support Thyme Care's mission in oncology care, while collaborating with stakeholders to enhance performance metrics and reporting.

The Sr. FWA Analyst identifies fraud, waste, and abuse in medical billing through data analysis, supporting engineering and data science teams with validation and tuning of detection algorithms.

As Senior Manager of IT Commercial Data Management, you will lead data initiatives, manage product ownership, and develop data governance strategies in collaboration with stakeholders, ensuring high data quality and analytics capabilities.

As a Senior Data & Analytics Engineer, you'll lead data initiatives, manage a team, and ensure data quality while turning insights into actionable decisions across the company.

Analyze sales data, build and maintain dashboards and scorecards (Power BI, Excel), evaluate market trends, employ AI/automation for pipeline and lead scoring, support sales leadership with actionable insights, document processes and collaborate cross‑functionally to improve sales performance and planning.