Top Remote Data & Analytics Jobs in Phoenix, AZ

The Data Engineer is responsible for designing data workflows and pipelines, implementing systems engineering principles, and deploying data streaming technologies while ensuring compliance with industry regulations and best practices.

As a Sr. Data Engineer at Lyra Health, you will build and scale core data infrastructure, design data warehouses, and create efficient data pipelines while collaborating across departments.

As a Director in the Data & Analytics team, you will lead client engagements, manage projects, develop strategies, create proposals, and mentor team members in data-driven initiatives.

The Marketing Data Scientist will analyze data, onboard clients, develop data pipelines in R, and propose improvements to enhance efficiency.

As a Data Scientist, you will analyze blockchain data to derive insights, develop and deploy predictive models, and improve product offerings.

Build reliable data models and semantic layer for AI-powered analyses. Support Product, Finance, and Customer Success with SQL-based analytics, BI dashboards, and stakeholder storytelling. Standardize data team processes, prioritize work, and collaborate across company to enable data-informed decisions.

The Senior Data Engineer will design and maintain data pipelines, write production-grade Python and SQL code, and support AI initiatives while collaborating across teams.

Lead the technical roadmap and hands-on development of a scalable data platform, build analytics and data access solutions, ensure data quality/governance/observability, mentor and grow a team of data engineers, collaborate cross-functionally, and evaluate new big-data technologies.

Entefy seeks a Senior Data Scientist with a Master's or PhD in a relevant field, and 3+ years of experience. Responsibilities include delivering advanced analytics, leading teams, and extracting insights from datasets.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.