Top Senior Data & Analytics Jobs in Rochester, NY

Leads actuarial technology and reporting initiatives, expanding adoption of the Actuarial Technology Platform. Designs and implements process improvements for financial reporting and pricing, develops process maps, supports legacy actuarial solutions, and promotes AI-enabled analytics. Collaborates with actuarial data, enterprise analytics, and platform teams while providing technical leadership, governance, issue resolution, training, and mentorship.

Build and maintain branch network performance reporting, dashboards, semantic models, and analytical datasets using SQL and Alteryx. Translate banker, branch, market, and enterprise data into actionable insights for senior leaders. Lead analytical projects, manage timelines, communicate executive-ready findings, improve reporting processes, and mentor junior analysts. Partner with Distribution and Consumer Bank leadership in a hybrid, primarily onsite environment.

Build and maintain data models, pipelines, metrics, dashboards, and analytics supporting Netflix’s advertising identity graph, entity matching, and identity resolution systems. Evaluate match quality, coverage, graph stability, and data drift; collaborate with engineering, data science, product, and identity providers; and communicate technical insights and trade-offs to technical and non-technical stakeholders.

Data Engineer II will modernize BlueLabs’ data platform by leading Kimball dimensional modeling and legacy warehouse migrations, building reliable production data pipelines, and enforcing data quality standards. The role requires advanced SQL, Python, and dbt expertise, hands-on Snowflake and Redshift experience, and ownership of testing, documentation, observability, and scalable architecture. The engineer will collaborate cross-functionally, guide Data Engineer I team members, contribute to architectural decisions, and translate business logic into maintainable, cloud-agnostic data layers.

Leads data intelligence for Medicaid, DSNP, and Marketplace procurement efforts. Analyzes claims, clinical, quality, network, operational, and competitive data; governs centralized repositories; develops proof points for RFPs; and provides strategic recommendations to proposal writers and growth leaders. Manages concurrent procurements, stakeholder relationships, reporting, continuous improvement, and staff development while supporting regulatory and competitive monitoring. Requires up to 40% business travel.

Own analytics and reporting solutions for acquisitions, product launches, and other complex business events. Translate business changes into data models, system updates, processes, and reporting definitions. Coordinate Data Engineering, Analytics, Data Science, and Data Governance teams; lead cross-functional execution and establish a Business Intelligence Council. Partner across GTM, Finance, Product, IT, and other functions to reconcile metrics, clarify ownership, and maintain business visibility.

Lead enterprise data engineering standards, governed pipelines, data contracts, observability, quality controls, lineage, testing, and compliant data delivery. Partner with governance, privacy, architecture, modeling, and platform teams to ensure reliable, traceable, protected data products. Monitor operational performance, automate deployment and validation, and resolve pipeline and data reliability issues across complex enterprise environments.

The AVP, Data Engineer will design and build data ingestion, transformation, and replication pipelines using SQL, Python, dbt, and Dagster. Responsibilities include translating requirements into technical designs, developing data products, debugging production issues, supporting testing, and improving data engineering practices. The role also involves data modeling, mentoring junior engineers, conducting code reviews, and providing technical leadership while remaining hands-on. Experience with modern data platforms, workflow orchestration, cloud ecosystems, and insurance or financial services is preferred.

Leads enterprise data architecture for a federal transportation agency, including data modeling, data warehouses, data marts, database design, ETL/ELT integration, governance, and cloud modernization. The role architects AWS-based solutions, supports migrations to Databricks and data lakes, integrates disparate systems, and provides technical leadership to stakeholders and development teams.

Develop and maintain Power BI reports, dashboards, visualizations, semantic models, and analytics solutions. Translate business requirements into scalable technical solutions, optimize queries and data models, ensure reporting accuracy and performance, and support data governance. Serve as the primary liaison for business users, provide training and troubleshooting, manage tickets, and collaborate with Data and QA teams. The role also advances AI and machine learning capabilities, mentors colleagues, and contributes to automation, documentation, and code reviews.