Top Remote Analysis Reporting Jobs in Santa Cruz, CA

Build and maintain governed gold-layer data products, semantic models, standardized metrics, Power BI reports, and AI-enabled experiences. Design and deploy RAG solutions, AI agents, embeddings, and automated workflows using Microsoft Fabric and Azure AI Foundry. Apply security, governance, monitoring, testing, deployment, and documentation standards. Own technical delivery from design through production support, conduct proofs of concept, mentor peers, and enable adoption across plant and business teams.

Lead the design and implementation of a scalable contract data model, including migration strategies, data architecture, pipelines, warehouses, analytics layers, governance, security, and quality monitoring. Partner with Product, Engineering, Data Science, ML, Professional Services, and customer-facing teams. Drive architecture decisions, provide technical mentorship, lead reviews, and manage multi-quarter data initiatives for a SaaS platform.

Leads enterprise data architecture and phased Microsoft Fabric implementation. Defines data models, integration patterns, governance standards, lineage, metadata, security, semantic layers, and scalable platform architecture. Partners with data engineering, IT, governance teams, business owners, analysts, and technology leaders to translate business requirements into sustainable technical solutions and support analytics, reporting, self-service, and AI enablement.

Leads Rocket Lawyer’s enterprise data organization, owning data strategy, architecture, platform modernization, governance, instrumentation, analytics tools, customer data, and AI enablement. The role manages cloud data infrastructure, batch and streaming pipelines, self-service analytics, privacy compliance, vendor decisions, and team development while partnering with the CTO and executive leadership.

Leads the architecture, development, and production operation of complex data pipelines and platforms. Resolves scalability, data quality, reliability, and architectural challenges; evaluates data technologies; mentors engineers; establishes engineering standards; partners with product, analytics, and operations teams; communicates technical trade-offs; and conducts proofs of concept to guide platform strategy.

Analyze marketplace and product data to identify growth opportunities, define and monitor core metrics, build dashboards, run experiments, size initiatives, and translate insights into actionable product and go-to-market decisions. The role partners with cross-functional leaders and stakeholders to measure impact and drive measurable outcomes.

Assists transplant nephrology investigators with collecting and managing research datasets, analyzing secondary data sources, and performing statistical and regression analyses. Generates tables, reports, and computations; maintains study records and files; and helps identify trends and educational needs. The role is part-time, remote, and requires basic computer systems and data analysis skills, with prior experience preferred but not required.

Analyze complex data to support company-wide decisions and responsible growth. Build metrics, data pipelines, dashboards, reports, and self-service tools; translate stakeholder needs into data problems; deliver actionable recommendations through analysis and storytelling; collaborate cross-functionally and enable teams to use data effectively.

Own supplier data quality through profiling, sampling, source linking, issue quantification, and quality monitoring. Partner with data engineering, product, and cross-functional teams to translate findings into technical improvements and prioritize opportunities. Build dashboards and reports to communicate data health, support automated quality gates, and apply customer insights to data and product improvements.

Develop and maintain data delivery processes, workflows, data quality solutions, and visualizations supporting consumer lending. Analyze complex datasets, identify root causes, resolve production issues, and provide actionable recommendations. Collaborate with technical and business stakeholders, document methodologies, and communicate findings effectively. The role requires SQL, Python, Tableau, cloud data environment, database, and large-scale dataset experience.