Top Remote Analysis Reporting Jobs in Rochester, NY

The Manufacturing Analytics Engineer will manage the analytics pipeline, transforming operational data from OT systems into actionable insights for decision-making, while collaborating with Engineering, IT, and Operations.

The Sr. Analytics Analyst will set up data feeds, create reports, perform data analysis, and ensure data quality for client implementations.

As an Associate Technical Architect, you will solve big data problems and develop solutions for migration, storage, and processing, focusing on Databricks and data engineering.

The Senior Data Engineer will design and maintain scalable data pipelines, lead medium-sized platform projects, and ensure reliability of data systems through monitoring and optimization. Responsibilities include working with cross-functional teams to improve data workflows and participate in incident response.

The role involves leading a systems analysis team for Oracle Cloud ERP in finance operations, ensuring process scalability and compliance, while mentoring team members and driving continuous improvement.

The Data Governance Leader will manage data governance engagements, align business and technical teams, implement governance processes, and coach staff on data stewardship.

The Analyst, Payments Risk- Shadow Risk Monitoring conducts merchant onboarding, risk reviews, and oversight of merchant risk monitoring while communicating with internal teams and clients.

This role involves defining data platform standards and integration patterns, mentoring engineers, and maintaining best practices in Azure and Databricks environments. The lead will ensure efficient data management and governance across global teams while advocating for DataOps and CI/CD practices.

The Actuary will drive pricing strategies, transform technical analyses into actionable insights, and support pricing processes while collaborating with cross-functional teams.

The Director of Data & Analytics will lead the Data & Analytics team, define product strategies, ensure quality outcomes, and drive user adoption of data products. They will act as a technical lead in customer interactions while balancing various internal and external data-related priorities.