Top Analysis Reporting Jobs in Tucson, AZ

Build and maintain reusable data structures, automated Microsoft Fabric pipelines, SQL logic, and governed reporting foundations. Modernize SSRS reporting by centralizing duplicated logic, troubleshoot data-quality and pipeline issues, and support traditional and AI-assisted business insights. Partner with technical and business stakeholders to translate recurring reporting needs into scalable solutions while maintaining documentation and operational practices.

Designs, deploys, maintains, scales, and supports enterprise database systems, primarily PostgreSQL in Linux environments. Responsibilities include database architecture, tuning, backup and recovery, failover, large-scale data management, ETL, operational support, testing with real data, and developing system features. The role also explores emerging technologies, supports customer facilities, and may contribute to cloud, DevOps, GIS, APIs, dashboards, and web development.

Develop and maintain Goodwill’s business intelligence environment, including dashboards, reports, data integrations, workflows, data quality controls, and automated reporting. Partner with organizational leaders to define metrics, support workforce development and retail analytics, migrate reporting solutions, document data systems, train users, and apply security and privacy standards. The role also evaluates emerging analytics and AI tools and translates business needs into sustainable technical solutions.

Processes, analyzes, and interprets geophysical data, especially electrical resistivity and seismic datasets. Troubleshoots data acquisition equipment, supports survey design and technical report writing, integrates GPS and surveying data, and completes project documentation. The role may include limited fieldwork, requires adherence to OSHA and MSHA safety requirements, and supports project engineers and senior management.

Administers and optimizes enterprise Oracle databases supporting global consular applications. Responsibilities include database operations, backup and recovery, replication, disaster recovery, performance tuning, security remediation, SQL and PL/SQL development, upgrades, migrations, monitoring, governance, documentation, and operational support for Oracle RAC, Data Guard, GoldenGate, and Oracle Linux environments.

Lead production of marine and anadromous species range maps under FWS standards. Aggregate, normalize, transform, and validate spatial data; analyze habitat intersections; coordinate review cycles with FWS and NOAA Fisheries subject matter experts; document quality assurance; and obtain government sign-off for deliverables.

Designs secure, scalable database and data-warehouse architectures; develops logical and physical data models, schemas, metadata, interfaces, and integration standards. Coordinates clustering, backup, recovery, load balancing, and availability strategies. Plans upgrades, recommends infrastructure and configuration improvements, and tests database structures and programs. Collaborates with architects, analysts, and project teams to align database solutions with business and technical requirements.

Design, build, and operate end-to-end data pipelines and models for healthcare claims and payer data. Responsibilities include ingestion, canonical and analytical data modeling, legacy process migration, data quality, testing, CI/CD, deployment, operations, incident response, tool integration, documentation, and onboarding new data sources. The role partners across ML, product, analytics, platform, operations, and customer teams while critically evaluating AI-generated engineering work.

Own end-to-end client data migrations: reverse-engineer legacy ETL, design and build Airflow DAGs and Spark jobs, validate and reconcile data at scale, document architecture and decisions, and coordinate cross-functional teams through go-live and hypercare.

Build and operate scalable batch and streaming data pipelines, dimensional models, ELT/ETL workflows, and trusted data products. Improve data quality, observability, reliability, performance, security, and cost efficiency across the cloud data platform. Partner with analytics, risk, finance, product, data science, and machine learning teams to support business and AI use cases. Lead technical initiatives, influence architecture, mentor engineers, and establish engineering best practices.

Own Mux’s end-to-end data platform, including ingestion, Snowflake administration, dbt transformations, orchestration, data quality, observability, and reverse ETL. Build semantic models supporting AI agents, establish governance and reliability standards, and partner with Engineering, Finance, Product, and GTM. Use AI coding tools to develop and maintain pipelines while validating output quality. The role requires strong SQL, Python, data modeling, cloud warehouse administration, and production data engineering experience.

Leads secure, scalable customer data architecture across Adobe Experience Platform and cloud environments. Designs data strategies, models, governance frameworks, ingestion and integration solutions, migrations, and real-time customer profiles. Partners with data engineers, Adobe, and clients to address data quality, security, privacy, performance, and regulatory requirements. Uses SQL, scripting, APIs, and Postman to support implementation and automation while providing technical leadership across multiple customer projects.