Top Remote Data & Analytics Jobs in Portland, ME

Implement and maintain ETL processes to ingest and transform hospital data into Meduit platforms. Build data models, ensure data integrity, document and track tasks in Jira, collaborate with cross-functional teams, support revenue-cycle data implementations, and mentor team members on best practices.

The Looker Data Engineer will build and optimize data models, develop reporting solutions, and support data-driven decisions using Looker and other technologies.

Perform geospatial wildfire hazard and risk modeling using fire behavior software and GIS. Calibrate fuelscapes and vegetation/canopy fuel layers, support nationwide risk assessments, translate fire workflows into software user stories, and collaborate with developers to test and deploy Wildfire Risk datasets.

Lead the architectural direction of Seer's data platform, mentor engineers, optimize data processes, and integrate AI solutions to enhance data-driven decision-making.

As a Credit Risk Senior Analyst at Marqeta, you'll lead underwriting strategies, refine credit policies, conduct risk analyses, and present findings to senior management.

Lead data strategy at Alpha, oversee data functions, build robust data systems, drive product decisions using data insights, and mentor a data team.

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 BI developer owning end-to-end reporting for marketing verticals. Build and standardize dashboards, model complex/third-party data (LookML), partner with Yield, Paid Media, and Account Management to deliver actionable analyses that optimize campaign performance, conversion, and revenue.

The Forward Deployed Data Engineer at ZoomInfo designs and delivers custom intelligence applications for strategic accounts, managing engagements end-to-end and collaborating with various teams to optimize data solutions.

Design, build, and maintain scalable batch and near-real-time data pipelines and data products using Databricks and Spark. Integrate internal/external sources, implement data models, ensure data quality, support BI (Sisense), CI/CD, and collaborate with analysts, scientists, and stakeholders to enable analytics and decision-making.