Top Remote Data & Analytics Jobs in San Luis Obispo, CA

The Principal Data Engineer will lead data architecture initiatives, design scalable data systems, and oversee data standards across teams while ensuring high-quality data infrastructure and guiding engineering teams.

Analyze conversational call flows and large datasets to optimize IVR and generative AI systems. Perform call testing, annotation, dashboard monitoring, and deliver data-driven insights and presentations to improve self-service, reduce agent handling, and enhance customer experience.

Design, build, and maintain an internal data platform and pipelines. Ensure secure, governed, resilient data access for engineering and BI teams. Partner with architects, implement automations, support platform consumption, mentor users, and drive continuous improvement and compliance.

The Senior Analyst will support product engineering efforts by analyzing digital solutions, enhancing user experiences, and collaborating across teams to deliver insights and improvements.

Own reconciliation and validation of client billing across internal systems, build repeatable data-quality checks and documentation, support Client Group with reporting and dashboards, investigate discrepancies, and drive process improvements and automation to reduce billing friction.

Design, develop, and optimize SQL-based data solutions and ETL pipelines in Microsoft SQL Server. Ensure data accuracy, performance tuning, validation, and documentation. Partner with delivery, engineering, and client teams, support production systems, participate in code reviews, and drive process improvements with minimal oversight.

Manage client-facing data and analytics projects: define data strategy, build automation and ETL, develop visualizations and predictive analytics, drive transformation, manage scope/budget, and communicate findings to non-technical stakeholders while leveraging finance knowledge.

Design, develop, and optimize Microsoft SQL Server data solutions and ETL pipelines. Build complex T-SQL queries, stored procedures, views, and performance optimizations. Ensure data quality, translate requirements into technical implementations, document logic, support production, and collaborate with delivery, engineering, and client teams.

Lead and build a measurement function from scratch: design infrastructure, write SQL and dashboards, define reporting playbooks, drive early insights, set pre-sale success metrics, own first- and third-party data, productize measurement as revenue, and hire and scale a technical measurement pod.

Provide technical and administrative support to leadership: monitor sprints and Scrum synchronizations, perform technical research, write Python scripts for automation and API testing, manage and report data using advanced Excel, and prepare meeting summaries and cross-functional coordination.