Top Data & Analytics Jobs in Rochester, NY

The Data Engineer at Anteriad will design, build, and optimize data pipelines, manage data integration processes, support analytics efforts, and collaborate with stakeholders to deliver scalable data solutions.

Lead Tilt's Business Intelligence function end-to-end: manage a distributed BI team, own reporting data models and semantic layer, build and maintain a metric-and-metadata library with reference SQL, review dbt work and hold quality through code review, prioritize stakeholder requests, and grow team technical and business fluency.

Lead data management for Hilton measurement and reporting: ensure data quality and taxonomy governance, build and maintain multi-source data integrations and connectors, transition reports to Power BI dashboards, support MMM workstreams, and serve as the client-facing data lead while collaborating with cross-functional analytics and account teams.

Lead and grow a data engineering team; define architecture and standards for ETL/ELT pipelines; hands-on design, code review, and development; ensure production reliability, monitoring, and incident response; partner with product and engineering on data roadmap.

Lead demand forecasting and performance analytics for eCommerce: build forecasting models, run scenario and promotional analyses, produce executive reporting, drive cross-functional predictive initiatives, and deliver market and competitive insights to inform planning and resource allocation.

Lead catastrophe risk analytics across lines, validate and customize Cat models, collaborate with underwriting/actuarial/finance to inform pricing and portfolio strategy, build Cat modeling workflows, mentor analytics staff, support live catastrophe events, and drive R&D on emerging risks and vendor/model calibration.

Analyze ad performance metrics (revenue, CPM, fill rates), produce regular reports, support yield and ad ops to optimize inventory across direct and programmatic channels, perform basic forecasting and scenario analysis, collaborate with cross-functional teams, and document insights and testing frameworks to improve monetization.

Define and govern enterprise data architecture, models, canonical and semantic layers, field-level mappings, and data governance. Partner with IT, Data Engineering, Security, and product teams to ensure data quality, lineage, integrations (Boomi), and platform alignment (Salesforce, Snowflake, NetSuite). Lead M&A data activities, perform hands-on data profiling and validation, and drive adoption of enterprise data standards to support analytics, AI, and automation initiatives.

Serve as embedded BI lead for a divisional sales book, delivering actionable insights from syndicated and commercial data, leading opportunity analysis, training field teams, supporting Power BI reporting, and translating complex data into executive presentations to drive sales performance and planning.

Lead design and implementation of end-to-end ELT pipelines and transformation layers (dbt) to produce curated, reporting-ready datasets. Define data models, governance, metadata, lineage, and engineering standards. Partner with cross-functional teams to translate requirements, optimize performance and costs (cloud DW like Snowflake), and grow a data architecture practice that supports BI, self-service analytics, and AI agents.