Top Senior Analysis Reporting Jobs in Rochester, NY

Administer enterprise SQL Server and Oracle databases, ensuring availability, performance, security, backup and disaster recovery. Design and maintain databases, clusters, governance documentation, reporting services, connectivity, and high-availability platforms. Perform capacity planning, monitoring, troubleshooting, patching, configuration, data integrity, and recovery testing. Coordinate with stakeholders on technical requirements, staffing, costs, long-term database planning, and continuity operations across multiple locations.

Lead enterprise Microsoft Fabric data architecture, landing-zone design, governance, security, integration, semantic modeling, DevOps, and AI-ready platform delivery. Design scalable Lakehouse and Warehouse solutions, establish standards and operating models, guide Power BI and data engineering practices, automate deployments, and provide technical leadership across architecture reviews, discovery workshops, and implementation. The role requires deep Azure, Fabric, data engineering, security, and enterprise integration expertise.

Lead account-level analytics strategy by translating client objectives, media performance, and cross-channel data into measurement plans, testing roadmaps, dashboards, and actionable recommendations. The role requires client-facing data storytelling, BI and SQL proficiency, quantitative analysis, quality control, and collaboration with media and strategy teams to improve marketing decisions and measurement effectiveness.

Build and operate production pipelines for legal records from PACER, court systems, opinions, PDFs, scans, XML, and HTML. Develop LLM-assisted extraction workflows, validate data quality, optimize SQL, and support RAG and semantic search products. Manage AWS S3 and RDS systems within security guardrails while collaborating with engineering teams. The role requires strong Python and SQL skills, legal data experience, document extraction expertise, and autonomous problem-solving with large, messy datasets.

Leads digital and marketing analytics for customer acquisition across multiple lending brands. Owns performance reporting, measurement frameworks, data governance, attribution and marketing effectiveness models, funnel analytics, experimentation, dashboards, and executive insights. Partners with Marketing, Risk, Finance, Operations, Technology, Engineering, and Data teams to optimize conversion, ROI, customer journeys, and data infrastructure. Requires advanced SQL, web analytics, statistical analysis, experimentation, and marketing measurement expertise.

Leads analytics, reporting, data modeling, automation, AI-agent development, and quality assurance for revenue cycle operations. Creates Power BI and Excel reports, analyzes complex healthcare and operational datasets, develops scalable warehouse models, and delivers actionable insights to leadership. Uses SQL, cloud data platforms, Git, Python, and AI-assisted tools to improve reporting efficiency, accuracy, and decision support.

Develop and maintain reports, dashboards, KPIs, and executive insights using SQL, Power BI, and other BI tools. Reconcile operational and financial data, investigate anomalies, ensure reporting quality, and document data models, metadata, governance, and reporting inventories. The role also performs advanced data manipulation, visualization, data storytelling, and analytical recommendations. Fraud and disputes domain knowledge is preferred.

Leads architecture and hands-on development of scalable data pipelines, governed data models, semantic layers, analytics products, and AI workflows. Writes production SQL and Python, establishes engineering standards, mentors engineers, and drives design reviews. Builds agentic and LLM solutions using retrieval and managed AI services while ensuring data quality, observability, reliability, privacy, and regulatory compliance for PHI and genomic data. Partners with stakeholders, platform teams, and governance forums to deliver trustworthy business solutions.

Leads analytics and data engineering for Sales and Revenue Operations. Builds reporting in Looker and Snowflake, manages CRM data flows into cloud warehouses, establishes transformation and modeling layers, and develops forecasts, scoring, churn, and expansion models. Supports territory, quota, pricing, and revenue-truth initiatives while presenting insights to finance and company leadership.

Analyze product, user, transactional, and repayment data to develop risk and underwriting models, reduce losses and fraud, monitor model performance, and guide product and growth strategy. Build Looker dashboards and LookML models, conduct segmentation and experimentation, measure CAC and LTV, and communicate actionable insights to product, engineering, marketing, finance, and leadership.