Top Data & Analytics Jobs in Albuquerque, NM

Lead post-sales and revenue analytics by integrating product telemetry, support signals, and revenue data. Build scalable data models, reusable datasets, and semantic layers. Define SaaS metrics, forecast revenue and usage, predict expansion and churn, and deliver dashboards and insights to drive renewals, expansion, and revenue growth.

The Data Migration Specialist will ensure successful data transitions from legacy systems, engage in ETL processes, and provide customer support throughout the migration journey.

Lead data strategy for Stripe's risk product, design metrics and frameworks, manage data reliability, mentor analysts, and evaluate risk experimentations.

Own operational health, governance, and integrity of GTM customer and prospect data across Salesforce, Marketo, Demandbase and integrated systems. Implement data quality programs, manage enrichment and integrations, troubleshoot sync failures, support segmentation and reporting, document standards, and enable scalable automation and AI workflows to support Marketing, Sales, Customer Success, and Analytics.

The Senior Analytics Engineering Manager will oversee analytics engineering vision, manage a team, ensure data quality, and drive data-driven decisions across departments.

As a Quantitative Researcher, apply economic and statistical models to large-scale data, collaborating to solve quantitative challenges across industries.

Build and maintain ETL/ELT data pipelines and storage for batch and real-time use. Partner with product and engineering to define requirements, ensure data quality, monitor pipeline health, integrate cloud data warehouses/lakes, optimize SQL/Python transformations, and document data flows and architecture.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

Responsible for designing, developing, and maintaining scalable data pipelines and infrastructure, implementing data governance, and collaborating with teams to meet data needs.

Design and own end-to-end Databricks Lakehouse and AI/BI solutions across cloud platforms. Provide architecture, presales support, POCs, integration, estimations, mentorship, and technical leadership for multi-team deliveries, including batch and streaming data pipelines and GenAI integrations.