Top Analysis Reporting Jobs in Albuquerque, NM

As a Senior Data Analyst, you will analyze game telemetry data, translate business needs into insights, and guide technical teams. You will also lead exploratory data analysis and maintain data quality practices.

Design, build, and maintain scalable, secure data architectures, models, and ETL pipelines. Integrate diverse data sources, optimize performance and data quality, implement governance, monitor production SLAs, and collaborate with data scientists, analysts, and product teams. Provide technical leadership, documentation, and training to improve engineering practices across the organization.

Lead development of cloud data platforms and end-to-end data pipelines using AWS/Snowflake and big-data technologies (Spark, Hive, Iceberg). Automate builds and deployments with Bash/Python shell scripting, apply CI/CD and Medallion Architecture, perform data modeling and warehousing, and collaborate across teams. Pharma/AbbVie experience preferred.

Support data collection, cleaning, and preliminary analysis. Write and run SQL queries, use statistical tools and Python, produce visualizations, document methods, troubleshoot analytics tools, and collaborate with cross-functional teams to deliver actionable insights.

Lead credit underwriting, pricing, verification, and portfolio performance for personal loans. Use data and ML/AI to design automated decisioning, manage credit/fraud risk, forecast losses, and present strategies to leadership and investors. Collaborate cross-functionally and build vendor/alternative-data strategies to drive profitable growth while keeping losses within risk appetite.

Lead a small analytics team to produce data-driven insights for marketing and media optimization. Mine proprietary datasets, apply statistical methods, forecast KPI impacts, monitor business metrics, and act as liaison between business and technical teams to drive profitable media and client growth.

Analyze high-scale payment funnel and transactional data to identify conversion bottlenecks, design and evaluate A/B tests, define metrics and measurement frameworks, monitor product performance via dashboards, and translate insights into prioritized product recommendations in partnership with Product and Engineering.

Lead design and implementation of end-to-end ELT pipelines and transformation layers (dbt) to produce curated, reporting-ready datasets. Define data models, governance, metadata, lineage, and engineering standards. Partner with cross-functional teams to translate requirements, optimize performance and costs (cloud DW like Snowflake), and grow a data architecture practice that supports BI, self-service analytics, and AI agents.

Lead architecture and operations for the end-to-end data lifecycle: pipeline orchestration, dbt projects, cloud warehouse performance, dimensional modeling, data observability, HIPAA controls, and platform governance. Mentor a distributed data engineering team, partner with Analytics and Finance, and prioritize durable platform capabilities that enable BI, experimentation, and AI use cases.

Lead business intelligence efforts to analyze complex data, define KPIs, identify operational inefficiencies, and recommend process improvements. Collaborate with cross-functional teams and executives to implement data-driven strategies, manage improvement projects, monitor resource allocation, and ensure compliance with policies and regulations.