Top Senior Data & Analytics Jobs in Albuquerque, NM

Serve as a client-facing consultant translating business needs into technical specifications, delivering Liquid Data platform solutions, developing reports/dashboards, supporting implementations, and driving technology adoption while collaborating with internal teams and leveraging cloud, API, and BI integrations.

Lead Oracle Cloud reporting initiatives, ensuring data accuracy and performance while mentoring junior analysts and collaborating with stakeholders.

The Analytics Lead will guide data-driven decision-making, develop measurement frameworks, forecast revenue, and mentor an analytics team, ensuring effective communication of insights.

Senior individual contributor owning partnerships analytics: lead agent acquisition and product analytics, build risk/commission debt models, define onboarding "aha" metrics, optimize funnels, enable self-serve analytics, integrate generative AI tooling, and mentor junior analysts.

As an Analytics Engineer, transform raw data into metrics, manage data pipelines, ensure data integrity, and collaborate with teams for analytics solutions.

Design and scale data infrastructure, ensure data quality and governance, collaborate with teams on data products, and modernize practices.

The ETL Developer will design, develop, and test ETL scripts using the Informatica platform, gather requirements, and maintain database applications. They will also provide end-user support post-deployment and ensure requirement fulfillment.

The Senior Korean Linguist manages translation and copy-editing tasks, coordinates with freelancers, and ensures high-quality Korean-language deliverables while improving workflows and supporting quality efforts.

Design and maintain data systems for business-critical insights, connect data across platforms, build ETLs, and support business data decisions.

Perform data extraction from SQL/NoSQL systems, validate and transform data, and run statistical and psychometric analyses (IRT, reliability, norming). Validate assessment logic, define quality metrics, design research and simulation studies, and present findings via reports and dashboards. Collaborate cross-functionally and maintain current psychometric and data engineering practices.