Top Remote Data & Analytics Jobs in Albuquerque, NM

Performs geospatial data management, analysis, visualization, and analytical modeling for government and commercial clients. Supports hazard identification, risk assessment, and risk reduction efforts using ArcGIS and Microsoft tools. Develops web, mobile, and desktop applications; tests, deploys, documents, and maintains solutions. This non-full-time, on-call role requires frequent travel and deployment to disaster recovery sites nationwide.

Manage end-to-end data operations, including collection, processing, delivery, pipeline optimization, and data quality monitoring. Collaborate with engineering, product, and operations teams to improve data workflows, identify inefficiencies, and implement scalable solutions. Analyze data to provide actionable insights for decision-making and AI model development while communicating technical issues to non-technical stakeholders.

Designs, develops, and maintains scalable ETL pipelines, data lakes, warehouses, and integrated data solutions. The role includes requirements analysis, Agile collaboration, testing, debugging, documentation, cloud data engineering, and optimization of reliable and performant systems. It requires strong Python, SQL, database, distributed processing, data engineering, software development, and cloud platform skills, along with effective communication and problem-solving abilities.

Lead data engineering initiatives that build scalable warehouses, pipelines, ETL/ELT processes, dashboards, and automated reporting workflows. Translate finance and operational needs into reliable data solutions, implement governance and quality practices, and support integrations, migrations, acquisitions, and system enhancements across portfolio companies. Partner directly with finance, accounting, analytics, and operational stakeholders to improve decision-making.

Manage MSSQL and PostgreSQL databases, including installation, configuration, monitoring, performance tuning, security, backup and recovery. Develop optimized SQL queries, stored procedures, triggers, and views. Use AWS services for database deployment and scaling, Git/GitHub for version control, and collaborate with developers and system administrators. Support data warehouse design, ETL processes, reporting requirements, and database troubleshooting.

Build and maintain production-grade dbt data models and pipelines across ingestion, transformation, and visualization. Develop reliable datasets supporting reporting, analysis, finance, revenue recognition, and company decision-making. Collaborate with Finance, Engineering, Sales, Product, and Marketing to understand data needs, improve manual workflows, validate data accuracy, and create scalable solutions using modern data tools.

Build and own analytics for Provider Operations, including funnel, coverage, quality, tiering, retention, forecasting, and rate strategy. Develop dashboards, recurring reports, quality frameworks, and forecasting models that support operational decisions. Partner with Recruiting, Calendar Operations, Product, Engineering, and Data teams to improve tools and instrumentation. Present actionable insights to leadership and drive adoption.

Senior Business Intelligence Analyst who develops and governs Power BI dashboards, analyzes clinic performance metrics, ensures reporting accuracy, and translates operational needs into technical requirements. The role manages BI projects end to end, prioritizes analytics tickets, presents insights to executive stakeholders, establishes reporting standards, contributes to data-model requirements, and mentors junior analysts across clinical and corporate operations.

Lead data architecture for NAVSUP OIS, including database design, data modeling, warehouse strategy, ETL/ELT pipelines, migration, security, retention, backup, recovery, and performance optimization. Coordinate cloud and containerized environments, guide data engineers and DBAs, and support modernization from Oracle to cloud and analytical platforms. The role also provides technical leadership, architecture planning, integration, risk assessment, and policy development for mission-critical systems.

Customer-facing technical leader who architects, builds, and optimizes large-scale data engineering and lakehouse solutions on Databricks. Supports pre-sales and delivery with POCs, performance/load testing, workload sizing, migrations, observability, and adoption through workshops and community engagement.