Top Analysis Reporting Jobs in San Luis Obispo, CA

Develops and maintains dashboards, reports, data tools, and data infrastructure for Consulting. Analyzes client, project, portfolio, capacity, compliance, and outcomes data to identify trends and support decisions. Maintains data integrity across Salesforce, Resource Hero, Power BI, and related systems; establishes governance standards; trains staff; and manages consulting projects, workflows, budgets, timelines, and deliverables.

Leads a team of business and data analysts while owning the analytics roadmap for commercial, sales, and go-to-market functions. Translates business needs into analytical frameworks, KPIs, dashboards, models, and reporting strategies. Partners with senior stakeholders and cross-functional teams to drive data-informed decisions, governance, quality, and best practices. Provides mentorship, oversees solutions using modern data tools, and presents recommendations supporting planning, forecasting, and execution.

Analyzes ground laboratory and open-air flight test data for avionics, sensor, radar, and electronic warfare systems. Develops Python-based data processing pipelines, correlates TSPI and telemetry data, decodes avionics buses, evaluates system performance, identifies anomalies, and produces verification metrics, technical reports, and executive briefings supporting test and acquisition decisions.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

Analyze and model property catastrophe reinsurance treaties using catastrophe modeling platforms. Prepare and validate exposure data, execute models, interpret risk metrics, develop scenarios, and identify portfolio risk drivers. Support underwriting, actuarial pricing, placement, renewals, and management decisions through clear reporting. Participate in model validation, calibration, research, and development while collaborating with underwriters, actuaries, and other stakeholders.

Bridges business and technology teams by gathering requirements, analyzing processes and systems, documenting workflows, supporting implementations and integrations, developing test plans, assisting with user acceptance testing, resolving system issues, preparing stakeholder reports, and supporting business users through training and ongoing system improvements.

Design and deliver modern data platforms, scalable and secure ingestion and transformation pipelines, durable data models, streaming systems, and reporting layers. Partner directly with clients and business stakeholders to translate requirements into architecture, explain tradeoffs, and own delivery outcomes. The role includes production implementation across cloud data platforms, orchestration, governance, real-time technologies, and analytics or AI data consumption.

Collects and validates patient-level clinical data from primary care clinics, maintains run and SPC charts, prepares recurring reports, and supports PDSA improvement cycles. Uses Excel, Google Sheets, and AI tools to clean data, synthesize feedback, identify trends, and improve workflows. Collaborates with clinic staff, project leads, and partners while ensuring data integrity, HIPAA compliance, and accurate reporting.

Build and operate ETL and real-time pipelines connecting veterinary practice systems, billing platforms, and third-party APIs. Design data models and a warehouse supporting hospital analytics, finance, and reporting. Establish standards for testing, documentation, monitoring, and data quality, while troubleshooting production data issues. Partner with Finance to improve Sigma self-service reporting and define scalable integration patterns as the company’s first data engineer.

Leads the enterprise data strategy, builds and scales the Data & Analytics team, and oversees data warehouse modernization, migration, governance, KPI standardization, and data quality. Partners with executives and cross-functional teams to convert data into actionable insights, operational improvements, predictive analytics, and AI-enabled workflows. The role requires hands-on Python, SQL, cloud, machine learning, and ETL expertise, plus strong leadership and communication skills.