Top Senior Data & Analytics Jobs

The CPFR Analyst will enhance customer satisfaction by improving collaborative planning and driving continuous improvement initiatives within the supply chain. Responsibilities include analyzing forecasting trends, executing value-added services, identifying data insights, and collaborating with multiple functional teams.

The Senior Data Analyst will build dashboards, ensure metric quality, and provide insights to support decision-making across teams. Responsibilities include data analysis, problem framing, and collaborating with stakeholders to improve data utilization.

Lead analytics implementations using Google Analytics and Tag Manager for clients, providing mentorship and managing projects with a focus on enhancing clients' digital strategies.

As an Applied Research Engineer, you will drive the development of NLP systems, analyze data, collaborate with teams, and ensure efficient model integration.

The Data Engineer will design and build scalable data systems, support AI/ML integration, and collaborate across teams for the development of Canoe's Alts Data Platform.

Use large healthcare datasets to identify behavioral patterns, build product and client-facing analytics, partner with product and engineering to lead data projects from ingestion through analysis, and help shape data team strategy and recommendations.

Lead development and ownership of BigQuery data assets, pipelines, and observability. Build and optimize dbt models, CDC/file/streaming ingestion, and streaming replication. Partner with engineering and business teams to enable self-service analytics, advanced analytics (LTV, churn, attribution), and reliable real-time data products.

Seek a Lead Analytics Engineer to design and build scalable data solutions, oversee data engineering, and collaborate with cross-functional teams to meet data needs.

Lead Pager Health’s enterprise data and reporting strategy, build a centralized data and reporting shared services function, own internal dashboards and client-facing analytics, partner with Product and Engineering on data architecture and governance, mentor data teams, prioritize and deliver data initiatives, and drive continuous improvement in tooling, automation, and data storytelling to support growth, efficiency, and client outcomes.

Lead and grow a data engineering team that designs, builds, tests, and operates large-scale data pipelines and warehouses. Partner cross-functionally to translate requirements, ensure data quality, observability, SLAs, security, and governance, and drive automation and performance for analytics, ML, and product use cases.