Top Data & Analytics Jobs in Rochester, NY

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.

Design, build, and operate scalable batch and streaming data pipelines and a lakehouse on AWS. Implement ETL/ELT, CDC, metadata/catalog and governance, automated AWS provisioning (IaC), CI/CD for data pipelines, data quality and lineage, observability, and documentation while collaborating across teams.

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.

Join the BizOps & Analytics team embedded in a core business area to define problems, build analyses and reports, design experiments, surface insights, and drive data-informed decisions end-to-end to increase customer growth and business scale.

The Sr. Data Engineer designs ETL solutions and data architecture, collaborates on technical solutions, and addresses data management functions.

Embed with a core business area to define problems, build metrics, run analyses and experiments, generate actionable insights, and drive product, growth, AI, or partnership outcomes end-to-end.

Lead a team supporting Epic analytics and clinical/operational systems. Oversee daily operations, project coordination, testing, reporting, data governance, staffing, training, and vendor interactions. Design scalable data models and pipelines (Microsoft Fabric, SQL Server, Power BI), ensure data quality, and present findings to executive stakeholders while maintaining system availability and compliance.