Top Remote Analysis Reporting Jobs in Tucson, AZ

Own lightweight data governance and operational reporting: define/document business terms, maintain a data catalog, build SQL-based operational datasets and reports, monitor data quality, diagnose anomalies, and align stakeholders across BizTech, Analytics, and business teams.

Build and maintain cloud data pipelines and ML feature/model workflows in Snowflake and AWS. Implement data ingestion, transformations, quality checks, monitoring, and documentation. Collaborate with data scientists, analysts, and product teams to support analytics, audience insights, rapid prototyping, and reliable production deployments.

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.

The Junior Manual QA Engineer will execute test cases, perform exploratory testing, document bugs, and collaborate with teams to ensure high-quality software. This role involves learning QA methodologies and improving testing processes alongside experienced professionals.

The Data Analyst will build data pipelines, analyze complex datasets, and provide insights to support decision-making across multiple stakeholders in GFiber.

The Business Analyst will gather, analyze, and document requirements for health IT solutions, support UAT, and collaborate with stakeholders to improve processes.

The Senior Business Analyst collaborates with stakeholders to optimize Oracle Fusion solutions for Supply Chain Management, focusing on Order Management and Procurement, ensuring process integration and functionality. Responsibilities include requirements gathering, configuration, testing, and supporting post-go-live improvements.

The Data Migration Engineer will design and execute SQL-based ETL processes for migrating public safety data, ensuring high-quality data integration and collaboration with internal and external teams.

The role involves project management, efficiency analysis, quality assurance, and systems management with a focus on improving operational workflows and processes.

Lead data architecture and strategy across product, data science, and engineering. Design cloud-centric, scalable data models, ETL/ingestion, governance, and AI/ML-ready analytics. Guide tooling selection, proofs-of-concept, data storage decisions, security/compliance, documentation, and mentor Data Platform team members to operationalize mission-critical data solutions.