Top Data & Analytics Jobs in Rochester, NY

Perform full-stack on-chain and product analytics: query on-chain data, profile ecosystem actors, benchmark protocols, define KPIs, build dashboards, and translate findings into actionable briefs for strategy, BD, product, and growth teams.

Perform advanced quantitative analyses, build and maintain dashboards and automated reports, collaborate across teams to drive data‑driven decisions, lead process improvements, and mentor junior analysts.

Drive commercial KPIs across Southeast Asia by analyzing performance metrics, delivering insights to senior leadership, guiding sales teams to opportunities, supporting commercial rollouts and ad-hoc campaigns, and collaborating with stakeholders.

The IT Senior Analyst will gather requirements, lead testing, manage integration projects, and mentor team members in a high-paced environment.

The Principal Data Platform Engineer leads the architecture and development of the enterprise data platform, focusing on analytics, data science, and AI/ML capabilities. They establish standards for data quality and observability, design data ingestion and processing patterns, and mentor team members to enhance technical capabilities.

Develop and maintain ETL solutions, optimize processes, validate data, and support production issues. Collaborate with analysts for efficient data integration.

Own and operate Databricks production pipelines for Sugar Predict: monitor, alert, incident response, SLA reporting, performance and cost optimizations, migrate legacy ETL, onboard tenants, enforce Delta Lake architecture and multi-tenant isolation, apply security and governance, enable observability, maintain runbooks, and support CI/CD and on-call rotations.

Own day-to-day Snowflake administration and the Sigma semantic layer; manage ingestion (Fivetran), dbt modeling scope, reverse-ETL to Salesforce/HubSpot/NetSuite, data quality SLAs, reporting and dashboards, partner with managed data vendors, design automation and reproducible month-end financial analytics, and drive analysis and experiments for AdOps, Sales, and Finance.

Lead a small data engineering team partnering with Engagement Marketing to build scalable ETL/ELT pipelines, ensure data quality, define marketing metrics, integrate trusted data with ad platforms, and drive the data roadmap to enable measurement and growth.

Develop queueing and discrete-event simulation models and predictive/statistical models to identify bottlenecks, forecast operational outcomes, and support decision-making for personnel vetting, industrial security, and counterintelligence. Validate and document models, run scenario and sensitivity analyses, collaborate with data engineers, present results to technical and non-technical stakeholders, and recommend process improvements while working in a classified environment.