Top Senior Data & Analytics Jobs in Rochester, NY

The Senior Data Engineer will construct and optimize data pipelines, work with cross-functional teams, ensure data quality and governance, and mentor junior engineers while leading advanced analytics initiatives.

Own and build the support reporting layer: ticket volume, SLA, resolution times, CSAT/CES/sentiment, and capacity. Produce dashboards and analyses for leadership and engineering, maintain data quality and governance, prioritize issues using multi-signal models, and surface Voice of Customer trends to close the loop with Product and GTM.

Lead end-to-end encounter data management for CMS/state Medicaid submissions. Validate and optimize ETL converting source data into HIPAA X12 837P, support regulatory audits, analyze trends and root causes, liaise across business/technical/operations teams, and recommend process improvements to ensure compliance and data integrity.

Lead cross-functional analyses and build scalable reporting for go-to-market teams. Develop and automate data pipelines, create interactive dashboards, improve data quality, and translate complex findings into actionable recommendations for stakeholders and executives.

Design and build complex dashboards and interactive visualizations in Power BI and SAP SAC; integrate and model data from SAP BW, SAP HANA, and SQL; develop planning models and advanced formulas for financial/operational planning; gather requirements from stakeholders; optimize dashboard performance, manage data pipelines, and maintain report stability.

Lead development of scalable marketing data models, pipelines, and BI solutions. Partner with Marketing to define metrics, build dashboards, enable self-service analytics, and drive data governance and best practices.

Design, build, and maintain scalable data pipelines, lakes, and infrastructure using Databricks, Spark, Python, and AWS. Collaborate with ML engineers, data scientists, and analysts to deliver data products, ensure data quality and governance, implement DevOps/SDLC practices, mentor junior engineers, and evaluate new data technologies.

Architect, build, and maintain Snowflake-based ELT pipelines and production data models. Implement observability, data quality, and governance; optimize cost and freshness. Partner with Analytics, Product, and Engineering, use dbt/CI-CD and AI-assisted tooling, and participate in reviews and architecture planning to support analytics, BI, and ML.

Own and build customer health, usage/adoption, and product configuration data models. Produce ad-hoc and recurring analyses to identify upsell/expansion opportunities, partner with CS, Sales, Product, and Data teams, and present actionable insights to leadership to drive revenue-relevant actions.

Lead analytics work across operations, finance, clinical quality, and BD. Build and maintain BI tables and dashboards, ensure metric accuracy, run operational and growth analyses, support financial forecasting and partner reporting, and deliver ad-hoc analyses to improve efficiency, patient experience, and strategic decisions.