Top Data & Analytics Jobs in San Luis Obispo, CA

Lead the architecture and development of scalable AWS-based data ingestion, transformation, and orchestration pipelines. Build reliable data infrastructure using Python, SQL, Airflow, Lambda, ECS, SQS, and Terraform. Establish data modeling, quality, lineage, monitoring, testing, and observability practices while partnering with analysts, scientists, and backend engineers. Mentor senior engineers, guide technical decisions, and provide hands-on leadership for complex data platform initiatives.

Build and lead Ashley’s consumer insights capability, including research roadmaps, custom qualitative and quantitative studies, insights repositories, prioritization processes, and executive-ready storytelling. Translate consumer, retail, marketplace, feedback, and business data into actionable recommendations for product, marketing, merchandising, pricing, and growth decisions. Influence cross-functional stakeholders, develop AI-enabled synthesis workflows, and manage one direct report while operating resourcefully with imperfect data.

Own end-to-end product analytics: define questions and success metrics, run A/B tests, build dashboards and reusable SQL/Python analyses, investigate performance changes, and collaborate with Product, ML, and Data teams to inform product decisions.

Build, deploy, and operate production-grade data pipelines and data products for healthcare audiences. Design transformations, data models, and governed views using Python, SQL, Airflow, S3, Snowflake, and EMR. Implement data-quality, monitoring, and privacy-by-design controls for PHI/PII. Partner with product, analytics, and platform teams to onboard sources, support audience discovery, segmentation, activation, measurement, and troubleshoot production issues.

Lead the design and operation of automated compliance monitoring for consumer lending: translate regulations into rule-based data checks, own exam and audit data requests, triage exceptions, drive automation, steward compliance data, and provide technical mentorship to a supporting analyst. Produce audit-ready, reproducible evidence for regulators, bank partners, auditors, and senior leadership.

Lead advanced analytics for countrywide insurance product programs: build dashboards and monitoring frameworks, conduct deep-dive analyses and predictive modeling, identify systemic process and data gaps, partner with product and cross-functional teams, and influence strategic decisions to improve growth, retention, and profitability.

Build and maintain Tableau dashboards, define KPIs, validate data, and query large datasets with SQL. Analyze cross-channel marketing performance across paid media, CRM, ecommerce, web, and app channels. Translate findings into actionable business insights, recurring client reports, and executive-ready presentations. Collaborate with engineering, analytics, data engineering, and strategy teams while guiding stakeholders toward data-driven decisions.

Partner with Sales, RevOps, Finance, and Data Engineering to convert CRM and pipeline data into actionable insights. Build and maintain pipeline and forecasting reports, dashboards, and metrics; identify risks and opportunities; improve data quality and reporting reliability; triage analytics requests; and embed AI tooling into analytics workflows to accelerate output and ensure analytical rigor.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

The Senior Business Systems Analyst will leverage ServiceNow for automation, aligning solutions with business needs, enhancing user experience and driving AI-assisted solutions.