Top Remote Data & Analytics Jobs in Albuquerque, NM

Design, build, and maintain scalable data pipelines, lakes, and infrastructure using Databricks, Spark, Python, and AWS. Collaborate with ML engineers, data scientists, and analysts to deliver data products, ensure data quality and governance, implement DevOps/SDLC practices, mentor junior engineers, and evaluate new data technologies.

Analyze user behavior, feature adoption, and retention across a B2B SaaS platform to generate evidence-based product insights. Track journeys, run cohort and funnel analyses, support A/B testing, define product KPIs, ensure data accuracy, and provide structured recommendations to inform roadmap and improve adoption and retention.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

Architect, build, and maintain Snowflake-based ELT pipelines and production data models. Implement observability, data quality, and governance; optimize cost and freshness. Partner with Analytics, Product, and Engineering, use dbt/CI-CD and AI-assisted tooling, and participate in reviews and architecture planning to support analytics, BI, and ML.

Lead workforce planning, capacity modeling, and operational reporting to support staffing and forecasting. Build automated reports, dashboards, and analyses to identify trends and staffing gaps. Partner with operations, talent acquisition, and finance to validate assumptions, support projects, and provide actionable recommendations for workforce decisions.

Senior Power BI developer responsible for building dashboards, scorecards, and analyses that deliver actionable insights. Partner with stakeholders and data architecture to join disparate datasets, ensure data quality, perform ETL, apply advanced DAX/Power Query and SQL, and present recommendations to senior leadership to drive KPI improvements.

Use syndicated data (SPINS, Nielsen) and internal data to generate category and retailer insights, support forecasting, lead recurring and ad-hoc analyses, and deliver clear recommendations and dashboards to inform sales, category management, and cross-functional strategy.

Build and maintain Sekai's analytics transformation layer: design canonical datasets, define company-wide metrics, implement data quality and freshness checks, support experimentation and cohort/funnel analysis, and partner with product and engineering to improve instrumentation and analytics tooling.

The Data Scientist will work on data analysis, visualization, and reporting, utilizing various tools to assist stakeholders' needs.

The Senior Director will establish and lead the Real-World Data & Analytics group, oversee RWD strategy, engage in complex analytics projects, and build a high-performing team in the oncology domain.