Top Analysis Reporting Jobs in San Luis Obispo, CA

Profiles and analyzes data sources, documents end-to-end lineage, maps source data to canonical models, and supports API schema design. Develops data quality, validation, metadata, and governance documentation while collaborating with engineers, architects, clients, and stakeholders to define clear technical requirements for enterprise data products, APIs, and analytics.

Own end-to-end data platform architecture across ingestion, transformation, modeling, and serving. Improve warehouse efficiency, access control, reliability, observability, orchestration, CI/CD, and developer experience. Lead cross-functional technical initiatives, build monitoring and alerting, mentor engineers, guide architectural decisions, and develop AI-powered data tooling. The role requires strong SQL and Python skills, production experience with Airflow, BigQuery, and containerized infrastructure, plus architectural ownership and stakeholder communication.

Design and optimize Snowflake data warehouses, dbt transformation models, and scalable ETL/ELT pipelines. Develop ingestion utilities, improve SQL and warehouse performance, establish data quality and governance controls, and maintain CI/CD workflows using Git. Collaborate with analysts, data scientists, and business stakeholders across manufacturing, supply chain, and operations. The role also supports modern DataOps practices and may involve orchestration tools and cloud platforms.

Article about J. Major’s Bridal Boutique, highlighting its personalized bridal styling, inclusive customer service, designer gown selection, transparent pricing, appointment-based consultations, fitting support, order follow-through, and referrals to trusted alteration specialists. The boutique emphasizes a warm, judgment-free experience and relationship-centered service for brides.

Designs, builds, tests, maintains, and optimizes large-scale data pipelines, ETL processes, ingestion workflows, and cloud data storage. Develops Databricks data engineering and AI/ML pipelines, Azure Data Lake solutions, Power BI dashboards, and CI/CD automation. Ensures data quality, security, scalability, cost efficiency, and reusable engineering practices while collaborating with distributed technical teams.

Leads enterprise business intelligence and analytics solutions using Power BI and Microsoft Fabric. Designs semantic models, certified datasets, dashboards, DAX calculations, data transformations, security controls, and governed self-service analytics. Assesses and modernizes reporting portfolios, develops predictive and forecasting capabilities, gathers requirements, validates data quality, supports documentation and adoption, and mentors analysts. Collaborates with business, engineering, governance, and security stakeholders to establish scalable enterprise analytics standards.

Designs, builds, deploys, and maintains scalable data architectures, databases, ETL/ELT pipelines, API integrations, and cloud data solutions in AWS GovCloud. Migrates on-premises databases to cloud platforms, optimizes data models and performance, implements governance and security controls, and supports reporting and analytics. Collaborates with architects, data scientists, and stakeholders while documenting systems and conducting integration, validation, cost, and risk assessments.

Manages and evolves enterprise data lakes and warehouses, designing scalable AWS-based batch, CDC, and near-real-time ETL/ELT pipelines. Builds data quality, governance, lineage, security, monitoring, and recovery controls; optimizes Spark, Glue, Athena, Redshift, and S3 workloads. Develops reusable Python, SQL, and PySpark frameworks, supports schema evolution and analytical data modeling, and collaborates with business and technical stakeholders to deliver reliable data solutions.

Customer-facing technical leader who architects, builds, and optimizes large-scale data engineering and lakehouse solutions on Databricks. Supports pre-sales and delivery with POCs, performance/load testing, workload sizing, migrations, observability, and adoption through workshops and community engagement.

Own the Finance and Operations data layer, integrating systems into Snowflake and Omni, building reusable data models, dashboards, governed metrics, validation checks, and reconciliation workflows. Partner with Finance, Operations, and Data teams to translate business processes into trusted analytics, improve data quality, automate reporting, and support leadership decision-making.