Top Data & Analytics Jobs in Buffalo, NY

The Senior Data Engineer will build and maintain data pipelines, optimize data processing, and ensure data privacy and quality within the healthcare tech space.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

The Senior Analyst will support the personalization algorithm by conducting analyses, testing features, managing projects, and collaborating with teams to improve food recommendations for customers.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.

The Vehicle Data Editor will manage automotive data entry, ensuring completeness and accuracy by researching and interpreting data from OEMs and assisting in data cleanup projects.

The Assistant Manager will lead data governance and analytics initiatives, overseeing the data warehouse infrastructure, analytics processes, and ensuring compliance and quality in data management.

The Informatics Consultant translates health plan data into actionable insights for clients, collaborating with teams and managing requests effectively.

The Lead Snowflake Administrator will modernize the bank's data ecosystem, optimize Snowflake performance, oversee cloud engineering with Azure, implement governance, and lead cross-functional projects.

The role leads enterprise data governance and strategy execution by managing data working groups, ensuring data compliance, and translating data challenges into actionable solutions.

Support software engineers in software product development, manage project tasks, mentor team members, and ensure project delivery and innovation.

Lead data engineering efforts to build scalable ETL processes and data infrastructure, supporting cross-functional teams with reliable data and analytics.