Top Analysis Reporting Jobs in Rochester, NY

Supports IAA’s vehicle enhancement and make-ready program through recurring dashboards, baseline metrics, cost and vendor analysis, SLA tracking, workflow documentation, and process improvement. Identifies trends, risks, bottlenecks, and billing inefficiencies while preparing actionable recommendations and leadership materials to improve margin, cycle time, seller experience, and operational execution across branches and regions.

Leads and develops a team of Conversion Data Analysts, owning workload prioritization, delivery quality, and performance outcomes. Uses KPIs and data to identify risks, guide decisions, and improve high-volume conversion workflows. Partners with project management, Engineering, Product, Support, and leadership to ensure accurate data mapping and successful customer onboarding. Requires people leadership, SQL, Excel, data validation, CRM, and conversion tooling experience.

Design, build, and maintain Keboola-based data pipelines integrating multiple business systems to deliver accurate, scalable data for supply chain, logistics, and transportation analytics; collaborate with analysts and engineers; support documentation, governance, and pipeline automation.

Analyze operational data, build and maintain reporting models, KPIs, dashboards and scorecards. Provide actionable insights to improve network performance and customer experience. Prepare presentations for leadership, collaborate with cross-functional teams, and recommend operational efficiency improvements while maintaining BI best practices and continuing education.

Supports reporting, data analysis, dashboard development, data collection, quality assurance, and data warehousing initiatives. Cleans and analyzes data, generates actionable insights, communicates findings to nontechnical stakeholders, responds to data requests, and partners with KIPP program teams. The role also contributes to network events, team operations, and equity-focused culture development.

Supports IAA’s vehicle enhancement and make-ready program through recurring dashboards, baseline metrics, vendor and cost analysis, workflow documentation, process improvement, and leadership reporting. Tracks volume, cycle time, aging, completion, exceptions, SLA performance, utilization, and cost variances to identify operational risks and recommend improvements that support efficiency, margin, seller experience, and GTV growth.

Designs and scales cloud-native data platforms and ingestion pipelines using AWS, Databricks, and Spark. Builds APIs, file-upload mechanisms, ETL/ELT workflows, data transformations, and Lakehouse architecture supporting analytics, machine learning, and operational use cases. Provides operational support for legacy C# .NET ingestion processes, troubleshoots pipelines, and promotes data governance, security, reliability, and documentation in a multi-tenant SaaS environment.

Lead the architecture and implementation of enterprise-scale GCP data ecosystems, including PB-scale platforms and AWS-to-GCP migrations. Establish data platform roadmaps, self-service architectures, governance, security, quality, and Infrastructure as Code standards. Architect solutions using GCP data, analytics, AI, streaming, and containerization technologies. Lead cross-functional engineering teams, mentor staff, advise executives, manage technical risks, and communicate the business value of data initiatives.

Designs, implements, operates, and optimizes database and data-management systems supporting classified intelligence missions. Responsibilities include data architecture, SQL and NoSQL database administration, query and throughput optimization, ETL pipeline optimization, performance monitoring, capacity planning, documentation, backup and restore, audit logging, and continuity planning. The role requires onsite work in the Washington, DC region, U.S. citizenship, and a final Top Secret clearance with SCI eligibility or access.

Build and maintain scalable data solutions in Palantir Foundry, including ontologies, data assets, pipelines, workflows, analytics, and AI/ML applications. Translate stakeholder requirements into governed, secure, and maintainable solutions; troubleshoot platform issues; support data governance and cloud modernization; and create documentation, training, and user support resources for FAA platform users.