Top Analysis Reporting Jobs in Albuquerque, NM

Manage and optimize HubSpot CRM and related platforms to ensure accurate data collection, clean reporting, and consistent standards. Build and maintain workflows, automations, membership modules, campaign tracking (UTMs), and integrations with advertising platforms. Support hub teams on adoption, training, and actionable reporting to measure program impact.

Support large-scale voter contact programs by building and maintaining clean data tables, creating target audiences, prioritizing voting sites, running A/B test-ready segments, producing timely analyses and reports, and building automated processes and dashboards to surface real-time insights for program teams.

Lead clinical performance and outcomes reporting across facilities; analyze and distribute clinical data to support quality improvement, decision making, and resource utilization. Provide analytic leadership, train users, liaise with vendors, develop reporting processes, and support facility and enterprise quality and safety goals.

Design, build, and scale reliable batch and real-time data pipelines and warehouses. Partner with engineering, data science, and business teams to define data models, improve observability, optimize storage and querying, and evangelize data engineering best practices across the company.

Lead architecture and implementation of scalable data systems and pipelines from ingestion to delivery. Own ambiguous, high-impact integrations, improve data quality and reliability, adopt AI-augmented engineering, mentor engineers, and collaborate with Product, ML, and customer teams to ship production solutions.

Support FAA by developing, reviewing, and documenting metrics and dashboards for the National Airspace System. Work with large aviation datasets to perform data quality checks, queries, and automation. Create documentation, user guides, Confluence uploads, presentations, and reports for FAA leadership and industry stakeholders.

Perform sponsorship valuations through research, data modeling, analysis, and client presentations. Maintain valuation database, surface insights, refine methodology, and support strategy projects to inform sponsorship proposals and renewals.

Design, build, and maintain scalable batch and streaming data pipelines and analytics-ready data models. Implement cloud (primarily AWS) data platform solutions, data ingestion, transformation, orchestration, and observability. Embed data quality, governance, security, and metadata/lineage practices. Partner with architecture, analytics, and application teams to enable self-service analytics, reporting, and downstream use cases while driving platform evolution and engineering best practices (CI/CD, testing, documentation).

Design, build, and maintain scalable, fault-tolerant streaming data architectures and real-time pipelines using Kafka, MSK, and Kinesis. Implement stream processing, monitoring, security, IaC, and CI/CD. Collaborate with data teams, provide technical leadership, and optimize latency, throughput, and cost for real-time analytics and downstream systems.

Serve as the bridge between business stakeholders and development for internal data initiatives. Own intake, discovery, and requirements documentation for analytics, BI, and reporting. Write user stories, acceptance criteria, data definitions, and reporting logic. Maintain a prioritized backlog, support stakeholder validation of prototypes, participate in agile ceremonies, and resolve requirement gaps and risks to ensure development can execute independently.

The Senior Data Engineer will maintain and improve data infrastructure, design ETL processes, and create high-performance pipelines for analytics and AI initiatives using SQL and Python in cloud environments.