Top Analysis Reporting Jobs in San Luis Obispo, CA

The Senior Manager of Data Engineering will build a data platform, lead a team, and ensure data accessibility to support AI and business operations.

The Data Engineer will architect and develop robust data frameworks for data platforms, focusing on data transformations and automated workflows. Responsibilities include collaborating with stakeholders, ensuring data quality, and maintaining high engineering standards.

Lead design, build, and optimization of large-scale real-time and batch data ingestion and transformation pipelines. Integrate enterprise systems (SFDC, NetSuite, Workday), ensure data quality, observability, and reliability, and enable analytics/AI workflows. Architect solutions using Airflow, dbt, Python, Kafka, Snowflake, apply DevOps/CI-CD practices, mentor global teams, manage multiple projects, and align data engineering initiatives with product and business stakeholders.

Lead Finance Data & Analytics to build trusted data sources, governance, and analytics for Finance and cross-functional stakeholders. Manage analysts, drive data strategy and Snowflake data models, produce insights via SQL and Tableau, and deploy AI solutions to optimize finance decision-making and operations.

Lead Data Analyst responsible for advanced analytics, real-time dashboards, capacity modeling, and network performance insights. Collaborates with stakeholders to identify inefficiencies, run tests and pilots, and deliver actionable recommendations to improve service provider performance and network operations.

Design and build Toast’s enterprise analytics layer and AI-ready semantic layer in the data warehouse. Collaborate with domain teams and data engineering to implement hub-and-spoke architecture, define complex business logic in SQL, support scalability, partner with stakeholders, and provide technical mentorship.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

Partner with stakeholders to gather and document data requirements, translate needs into user stories and technical specs, perform SQL-based data analysis, source-to-target mapping, and validation, support data quality, lineage, and monitoring, serve as primary requirements contact, contribute to Agile ceremonies, assist change management and rollout, and maintain operational and client documentation.

Design and build data warehouse architecture, develop ETL/ELT pipelines, implement data governance, and partner with teams to improve data systems.

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 Forward Deployed Accountant leads the deployment of AI Agents for corporate accounting, trains teams, and ensures proper configuration and documentation of automated workflows.

Lead design and implementation of an enterprise Databricks lakehouse, build scalable batch and streaming pipelines, enforce governance and CI/CD standards, optimize Spark workloads, operationalize ML with MLflow, manage cloud infrastructure and IaC, and mentor data engineering teams.