Top Analysis Reporting Jobs in San Luis Obispo, CA

Lead architecture and delivery of enterprise data transformation on the Guidewire Data Platform. Drive design, ingestion/egress, migration performance, and AI-enabled tooling. Facilitate inception and design review sessions, mentor teams, coordinate with partners, and ensure successful data platform adoption and repeatable delivery practices while spending significant time on customer sites.

As a Data Engineer, you will design and maintain data pipelines, support DoD systems, and ensure data quality and compliance.

Own RevOps data models and BI infrastructure to drive GTM strategy. Clean and analyze datasets, build predictive models, define and track leading/lagging KPIs, deploy dashboards, document data definitions, and deliver executive-ready insights while partnering cross-functionally with Finance and GTM teams.

Lead and grow an analytics engineering team to build a trusted semantic metrics layer, scalable dimensional models, and governance. Partner cross-functionally to deliver reliable data products, improve pipelines and observability, set technical standards, and enable self-service analytics, experimentation, and ML while balancing scalability and business impact.

Design and implement data engineering and reporting solutions for MarTech/AdTech clients: build data models in BigQuery/dbt, manage ETL pipelines, create dashboards in Looker/Data Studio, validate integrations, and collaborate with product and engineering teams to scale reporting and analytics.

Process, validate and QA large survey datasets; produce datasets, tables, codeframes and documentation; support weighting, testing and statistical analyses; learn and apply Python/R, automation and AI-assisted tools; improve automated processing workflows under senior guidance.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Own and build customer health, usage/adoption, and product configuration data models. Produce ad-hoc and recurring analyses to identify upsell/expansion opportunities, partner with CS, Sales, Product, and Data teams, and present actionable insights to leadership to drive revenue-relevant actions.

Build and support high-performance data solutions, design and operate ETL pipelines and data warehouses, monitor production analytics tools, troubleshoot system issues, collaborate with product teams, and support TechOps for analytics infrastructure.

Design and own data migration strategy and architecture. Map source-to-target data models, build data dictionaries, perform migrations and testing, reconcile results, and collaborate with stakeholders and project teams to ensure successful modernization.