Top Remote Data & Analytics Jobs

Analyze healthcare and clinical operations data to deliver actionable customer insights, physician performance reporting, care-quality dashboards, and scalable BI solutions. The role requires SQL-based data transformation, dashboard development, collaboration with clinical, product, engineering, and client-facing teams, and clear communication of findings. The analyst will also use AI tools for query generation, data cleaning, pattern recognition, and analytical summaries.

Administer SQL Server and Azure SQL environments, including production operations, performance tuning, security, backups, migrations, upgrades, and troubleshooting. Support application development, database modeling, ETL, data warehouses, data marts, and Power BI environments. Collaborate with technical and business stakeholders, coordinate deployments, track issues, estimate work, and provide project updates while maintaining database availability and standards.

Build and maintain data lakes, data warehouses, and modern data pipelines for a multi-tenant SaaS platform. Design end-to-end data processes, write pipeline and infrastructure code, conduct design reviews, optimize performance, monitor systems, support data governance, and troubleshoot scalability and security issues. Collaborate with technical and business stakeholders, mentor junior engineers, evaluate technologies, document platform architecture, automate testing, and participate in on-call rotation.

Provide frontline production support for Oracle, Sybase ASE, and AWS data systems in DoD and GovCloud environments. Monitor databases and pipelines, investigate alerts and tickets, resolve routine incidents, perform backups, patching, access provisioning, and health checks, and escalate complex issues. Troubleshoot applications, authentication, login, and basic NGINX issues while maintaining runbooks and incident documentation. The role requires rotating 24/7 support, including nights, weekends, and holidays.

Own the architecture, roadmap, and operation of Clarium’s AWS-based data platform. Build reliable batch and near-real-time pipelines, model healthcare supply chain data, optimize Postgres and Snowflake performance, and establish standards for testing, deployment, quality, and governance. Partner cross-functionally to create durable data models, lead multi-quarter initiatives, manage sensitive data controls, and mentor engineers.

Leads and mentors the Data Engineering team while remaining hands-on in designing, building, and maintaining scalable data pipelines, warehouses, integrations, and infrastructure. Establishes architecture, reliability, quality, and performance standards; guides technical delivery; and resolves complex issues. Partners with Finance and business stakeholders to translate data needs into practical solutions, sets technical direction, evaluates technologies, and communicates strategy, risks, and recommendations to leadership.

Operates sUAS and processes high-resolution imagery to create photogrammetric products, geospatial datasets, maps, and scientific reports. Conducts habitat classification, vegetation and biomass assessment, elevation analysis, and change detection. Maintains drones, sensors, GNSS equipment, GIS geodatabases, metadata, and standard workflows. Supports field research in remote southeastern locations and collaborates with scientists and research partners on ecological monitoring and data publication.

Monitor prediction markets and perpetual futures by tracking news, trader sentiment, venues, volumes, open interest, funding rates, and market share. Research protocols and users, build dashboards and datasets, identify product opportunities for Pyth, size opportunities with market and on-chain data, and collaborate with product, engineering, and business development teams. Write research reports, present recommendations to leadership, and evaluate launched initiatives against their original theses.

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.

Build and operate core data infrastructure for edge and hybrid environments, including ingestion, OT/IoT integrations, real-time streaming, data contracts, schemas, validation, lineage, observability, telemetry, and scalable query access. The role requires production ownership, reliability practices, customer integration, and collaboration across engineering and customer-facing teams. Candidates should have 6+ years of experience with production data, streaming, or integration systems and proficiency in Python and/or Go.