Top Senior Data & Analytics Jobs in Albuquerque, NM

Build end-to-end data and analytics features: ingest and model data, build transformations and pipelines, create client-facing dashboards and interfaces, and develop LLM-powered workflows to accelerate analysis and app development. Partner with stakeholders, perform exploratory analyses, and ensure data quality, observability, and maintainability while influencing data engineering strategy.

The Staff Data Analyst will build Boulevard's product data foundation, create data-driven recommendations, develop dashboards, conduct deep analyses, and foster a data-driven culture within the organization.

Lead design and implementation of Snowflake-based data architectures; serve as primary Snowflake POC. Design performant Snowflake solutions (data sharing, clean rooms, virtual warehouses, micro-partitions, zero-copy clone, time travel, resource monitors, security). Tune SQL and queries. Work with data virtualization (Starburst, Denodo), Hadoop ecosystem, and build data lakes on Cloudera Data Platform. Strong written and verbal communication.

Design, build, and optimize end-to-end ETL/ELT pipelines using Python and PySpark for large structured and unstructured datasets. Ensure data quality through validation and reconciliation, troubleshoot performance issues, implement CI/CD and code review practices, and collaborate with IT and business stakeholders to translate requirements into scalable data solutions.

Lead and build Harvey’s people analytics function: design the people data architecture, consolidate HR systems, define metrics and methodology, create dashboards and forecasting models, surface leading indicators for intervention, enable self-serve analytics, and partner with People Ops, Recruiting, Finance, and Data Engineering to drive strategic workforce decisions.

Lead design, build, and maintain scalable batch and streaming data pipelines and data warehouse models. Ensure data quality, observability, performance, and security. Own workstreams, support production incidents, and enable analysts and downstream applications.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.

Design, support, and improve data analytics solutions (OAC and Power BI). Manage data ingestion, ETL, data quality, access, and documentation. Liaise with stakeholders, migrate dashboards from OAC to Power BI, and follow SDLC and project management practices.

Lead growth analytics for acquisition and activation funnels: measure channel performance, build data models and KPI reporting, run experiment analysis, and translate insights into business recommendations. Partner with Growth product team and leadership to visualize results and drive strategy.

Lead HR Service & Digital Experience analytics by owning reporting, ensuring data integrity, and translating operational and contractual HR data into actionable insights for senior leaders to improve caregiver and leader experiences.

The Manufacturing Analytics Engineer will manage the analytics pipeline, transforming operational data from OT systems into actionable insights for decision-making, while collaborating with Engineering, IT, and Operations.