Top Analysis Reporting Jobs in San Luis Obispo, CA

Build and maintain a global knowledge base of electronic-resource metadata. Responsibilities include analyzing publisher data, creating and maintaining collections, establishing data feeds, researching missing metadata, documenting transformation processes, resolving data issues through root-cause analysis, coordinating with vendors, and managing workload priorities. The role requires advanced Excel skills, attention to data quality, strong communication, and familiarity with metadata standards.

The Principal Data Engineer designs and builds scalable cloud-native data platforms, pipelines, frameworks, and governed data products supporting analytics, reporting, AI, and operational workloads. Responsibilities include Databricks, Spark, Delta Lake, Azure, SQL Server, batch and streaming processing, data integration, performance optimization, governance, modernization, troubleshooting, architecture reviews, and mentorship. The role provides senior technical leadership without direct people management and supports insurance-domain data across policy, claims, billing, finance, and regulatory functions.

Analyzes web, customer, and campaign data to generate actionable digital marketing insights. Builds dashboards and presentations using Adobe Analytics, Power BI, or Tableau; evaluates site performance, media monetization, A/B tests, and web projects; supports tagging, reporting validation, and vendor implementations. The role partners with stakeholders and Agile teams, manages analytics priorities, and communicates findings to guide marketing strategy and business decisions.

Leads enterprise data architecture strategy, modernization, and multi-year platform roadmaps. Defines standards for data models, ingestion, transformation, orchestration, quality, governance, observability, and consumption across batch and streaming environments. Provides technical leadership to data engineering and analytics teams, oversees scalable data solutions, mentors technical leaders, and partners with business, engineering, security, and data science stakeholders. Evaluates technologies, guides vendor selection, enables data products, and explores GenAI applications.

Leads the design, automation, optimization, and maintenance of scalable data pipelines using Airflow, dbt, Python, SQL, and Google Cloud technologies. Manages dbt models, develops reusable architecture patterns, monitors pipeline performance, supports CI/CD and testing, and ensures data security and governance. The role also provides technical leadership, mentors engineers, collaborates cross-functionally, documents implementations, and drives continuous improvement across data engineering practices.

Lead client analytics strategy, testing roadmaps, quantitative analysis, predictive modeling, campaign evaluation, reporting, and data visualization. Partner with cross-functional teams to deliver high-quality analytical solutions and communicate actionable insights to clients. Use statistical methods and tools including R, Python, SQL, BI platforms, and data warehouses to support marketing decisions, identify growth opportunities, and connect media performance to business outcomes.

Leads enterprise analytics strategy, data integration, governance, reporting, dashboards, forecasting, and advanced business analysis. Manages analysts and partners with Sales, Pricing, Finance, Product Management, Operations, and executive leadership to translate complex data into actionable recommendations. Oversees Power BI dashboards, KPI frameworks, data quality, predictive modeling, and reporting automation to improve growth, profitability, pricing, and operational performance.

Loads and validates hospital chargemaster and healthcare data into SQL databases using Excel templates and proprietary tools. Maintains databases, retrieves CMS data, prepares spreadsheets and reports, tracks client tasks, and supports financial analytics. Collaborates closely with clients and internal teams to ensure accurate, timely deliverables and provides client support. Requires knowledge of chargemaster elements, healthcare financial and patient accounting data, EHR systems, SQL, and advanced Excel proficiency.

Leads digital customer experience insights by translating behavioral, journey, Voice of Customer, and performance data into actionable recommendations. Maps end-to-end experiences, identifies friction and drop-off, maintains experience health dashboards, and partners with product, marketing, UX, and engineering on experimentation and optimization. Communicates findings to leadership and supports customer-first product decisions through analytics, competitive benchmarking, and proactive insight delivery.

Supervise actuarial predictive modeling initiatives for insurance pricing, portfolio management, and planning. Collaborate with actuaries, data scientists, underwriters, and management to develop, validate, govern, and implement models. Establish assumptions, loss adjustments, usage guardrails, monitoring practices, and model documentation. Support regulatory filings, improve team workflows, contribute to strategic projects, and mentor staff in actuarial and technical skills.