Top Remote Data & Analytics Jobs in Albuquerque, NM

The Senior Clinical Trials IT Business Analyst bridges Clinical Development and IT, optimizing clinical trial technologies and managing system implementations, validations, and stakeholder engagement.

Conduct AI-powered web research, scraping, market analysis, and lead generation to identify clients, partners, sponsors, investors, and collaborators. Build and maintain intelligence databases, automate research workflows, verify and enrich data, analyze unstructured information, prioritize opportunities, and present actionable recommendations to leadership.

Develop and maintain Palantir Foundry data pipelines, transformations, Ontology models, workflows, data products, and user-facing applications. Integrate structured and unstructured data from enterprise systems and cloud platforms using Python and SQL. Implement data quality, governance, metadata, lineage, testing, and validation practices while collaborating with technical and business stakeholders. Support Agile development, documentation, modernization, AI-enabled analytics, troubleshooting, and federal data solutions.

Designs and implements big-data data management solutions (Cloudera/Hortonworks/Databricks). Builds and automates reporting and analytics using SQL and Databricks, optimizes queries, manages ETL, integrates multiple data sources, enforces data governance, and supports payment integrity reporting requirements.

Designs, develops, and supports integration pipelines connecting SAP and non-SAP systems with SAP Datasphere and cloud data platforms, primarily Amazon Redshift. Builds data models, replication flows, ETL/ELT processes, and CDC integrations; monitors performance and data quality; applies governance and security standards; documents architectures; and collaborates with technical and business stakeholders to deliver scalable analytics solutions.

Clean, standardize, enrich, and import product data into the PIM while maintaining data integrity and governance standards. Oversee bulk ingestion processes, leverage AI and automation, support data model improvements, resolve product listing issues, and contribute to data hygiene and workflow modernization. The role also involves collaborating with client-facing teams, documenting processes, proofreading product data, communicating progress, and adapting to changing priorities.

Leads the architecture, design, and implementation of scalable GCP and Databricks data lakehouse platforms. Designs real-time and batch pipelines, data models, governance, cataloging, security, and performance optimization. Advises clients, translates business requirements into technical solutions, leads project teams, mentors engineers, reviews architectures, and balances strategic planning with hands-on proof-of-concept and troubleshooting work.

The Data Analyst gathers and documents data requirements, queries and analyzes data, validates reporting outputs, and supports KPI tracking. The role researches data sources, assists with ETL and enterprise data warehouse integration, maintains data dictionaries and lineage documentation, identifies quality issues, and delivers reports and insights to stakeholders. Additional responsibilities include supporting data governance, PII controls, master data management, reporting automation, and cross-functional solution design.

Owns enterprise-level analysis of client sentiment, health, retention, churn, and journey data. Develops measurement frameworks, health scores, executive dashboards, root-cause analyses, and leading indicators tied to revenue. Synthesizes qualitative and quantitative feedback, identifies systemic experience risks, supports lifecycle improvement initiatives, and presents data-backed recommendations to senior leaders and cross-functional teams.

Own paid social measurement and analytics across brand, consideration, and performance campaigns. Execute Conversion Lift and Brand Lift Studies, design geo-randomized experiments with data science, build KPI dashboards, evaluate creative and audience performance, and recommend budget and strategy changes. The role requires advanced SQL and Python or R, causal inference expertise, scalable reporting, and the ability to communicate insights to senior marketing leaders.