Top Remote Data & Analytics Jobs in Albuquerque, NM

Own pipeline reporting, revenue forecasting, pricing and deal-analysis frameworks, retention/renewal reporting, and marketing performance analysis. Create automated dashboards, partner with sales and engineering to maintain data pipelines, and present insights to commercial stakeholders to drive revenue growth.

Design, analyze, and document data products and technical specifications. Perform large-scale data profiling and SQL analysis, support data governance, partner with stakeholders to remediate issues, and help implement data quality, lineage, and ingestion standards.

Lead the RevOps analytics function: manage an analytics team, own revenue reporting and forecasting, build measurement frameworks, enforce data governance, partner with BI/engineering, analyze funnel and retention metrics, and embed AI/automation to improve revenue predictability and GTM performance.

Design, build, and operate secure, scalable cloud-native data platforms (lakehouse/data mesh) supporting batch, streaming, ML, GIS and operational workloads. Lead ingestion/transformation pipelines, distributed processing (Spark/Kafka), data governance, observability, and mentor teams while ensuring compliance in regulated environments.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

Embedded, senior technical engineer who designs and builds AI-ready, cloud-native data architectures using Alteryx One and major cloud data platforms. Convert analytics workflows into production solution patterns, deliver pilots-to-production quickly, enable partner-led delivery, and create documentation and playbooks for scalable deployments.

The role involves designing and owning the architecture of a workforce intelligence platform on Snowflake, leading architectural decisions, and ensuring compliance for a Marketplace listing.

As a Senior Data Scientist, you will develop machine learning models, optimize deployment processes, and collaborate with cross-functional teams to enhance clinical AI workflows.

The Analytics Manager analyzes complex datasets, builds models, conducts scenario analyses, and provides strategic recommendations to guide decision-making for leadership.

The Principal Data Engineer will lead data architecture initiatives, design scalable data systems, and oversee data standards across teams while ensuring high-quality data infrastructure and guiding engineering teams.