Top Data & Analytics Jobs in Albuquerque, NM

Hands-on engineering role to design, build, and maintain scalable ETL/ELT data pipelines, data warehouses and lakes, and data models. Optimize batch and near-real-time processing, implement query optimization and data quality checks, support AI data workflows, and collaborate with architects, analysts, and stakeholders.

Lead payments business intelligence and operational analytics: define KPIs, build and maintain dashboards, ensure data integrity and timely refreshes in Databricks/SQL, run financial and profitability analyses, develop pricing tools, support cross-functional operational reporting, and communicate actionable insights to Payments leadership.

Design, build, and optimize scalable cloud data pipelines and infrastructure. Maintain and refactor SQL and ETL processes, automate data workflows, ensure data quality/security, and troubleshoot complex issues. Provide technical leadership and mentor junior engineers while collaborating with stakeholders to translate requirements.

Lead technical design and delivery of Databricks lakehouse solutions: gather requirements, design and build scalable pipelines with Spark/PySpark and Python, integrate with cloud, enforce governance, optimize performance, lead code/review/testing/CI-CD, mentor engineers, and liaise with clients.

Design, implement, and maintain data quality processes using cloud platforms (Azure/AWS/GCP). Collaborate with stakeholders to define standards, perform data profiling and cleansing, document issues and remediation, generate quality metrics, and support cross-functional teams to improve data architectures and integration.

Analyze customer service performance for satellite teams, drive process and performance improvements, perform gap analysis, present insights to stakeholders, build reports and dashboards, support cross-functional projects, and assist the Customer Service team with issues.

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.