Top Remote Business Intelligence Jobs in San Diego, CA

Transform data into actionable insights by building dashboards, reports, and visualizations. Partner with cross-functional teams and data engineering to ensure data quality, lineage, and AI-ready metadata. Audit datasets, define monitoring rules, document data dictionaries, pilot AI-assisted BI tools, and apply hypothesis-driven analysis to surface insights that inform business decisions.

Build AI-augmented BI dashboards, semantic layers, and AI-ready metadata. Use AI-assisted tools to accelerate SQL and dashboard development, productionize ML outputs into BI, enforce data quality and governance, and present insights to business stakeholders including C-suite.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Lead GTM strategy and analytics to build headcount/capacity models, territory optimization, quota setting, predictive models, and BI reporting. Partner with Sales, Marketing, Finance, and Data to inform planning cycles, monitor pipeline and productivity, and deliver executive-level insights for growth and investment decisions.

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.

Act as a strategic partner to Revenue Operations by analyzing performance, building executive dashboards and reports, improving CRM data quality and governance, supporting forecasting and pipeline management, and designing scalable processes and automations to increase efficiency and revenue visibility.

Lead data product strategy and governance for customer-facing reporting within Managed Services. Own reporting product roadmap, data quality, standards, delivery platforms (Redwood Insights, BI, Snowflake, Excel), implementation readiness, and cross-functional alignment to scale trusted, automated customer analytics and reduce manual reporting.

Lead design and implementation of process and system improvements, perform data analysis and queries, produce BI reports, gather requirements, coordinate projects, and provide analytical insights to support healthcare business decisions. Work with databases, reporting tools, EPIC, Tableau and SAP, and communicate across organizational levels.

Lead integration of technology into information systems, design data warehouse and BI capabilities, define data architecture and dictionaries, centralize disparate data, design dashboards, document system architecture, perform data quality and management, and provide solution engineering, pilots, and enablement for analytics and resource management.

Lead enterprise data governance, quality, MDM, cleansing, validation, reconciliation, and migration efforts to support ERP implementations and large transformation programs. Develop governance frameworks, coordinate data readiness and testing, produce executive reporting and presentations, manage project plans and governance artifacts, and drive stakeholder alignment and change management.

Design and build Microsoft Fabric and Synapse analytics solutions (lakehouses, warehouses, pipelines, notebooks, semantic models). Develop Power BI reports and semantic models with DAX, performance tuning, and RLS. Integrate Dynamics 365/Dataverse data, author SQL/Python/PySpark transformations, manage source control and deployments, run client workshops, and build AI-enabled experiences.

The Director of Data and Enterprise Applications oversees the architecture, development, and support of business applications and data platforms, driving digital transformation and ensuring data integrity and accessibility.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Build and maintain BI dashboards and KPI reporting for manufacturing, supply chain, quality, and fulfillment. Create internal tools and workflow automations, integrate APIs and business systems, and consolidate ERP/MES/PLM data into unified operational reporting tied to recurring decisions.

Own end-to-end marketing and business intelligence: build automated dashboards (Domo), query large datasets (SQL/Snowflake), report subscription funnel economics, analyze channel performance and A/B tests, troubleshoot data anomalies, and partner with leadership to set KPIs and prioritize analytics work.

Support and develop BI applications for a client financial platform across environments. Build reports, analytics, and budgeting solutions (TM1), develop/tune Oracle SQL/PLSQL, deploy BI tooling, support UIs (low-code), follow Agile practices, and collaborate on integrations, security hardening, and operations.

Lead cross-functional analytics to inform clinical and operational decisions: build Tableau dashboards, create dbt analytical models, analyze large healthcare datasets (claims, EHR, HIE) with SQL, respond to ad-hoc requests via JIRA, and collaborate with product and engineering to improve data capabilities.

Design, develop, and maintain enterprise Power BI dashboards and reports. Integrate data from SQL Server, Azure, Excel and other sources, perform data modeling and DAX calculations, validate data, and document data models and reporting logic while partnering with business stakeholders.

Lead BI & analytics delivery for clients: manage BI analysts, oversee data mapping, governance, tabular models, dashboards, and reporting. Partner with clients and engineering to develop analytics roadmaps, optimize Power BI models, automate data workflows, and drive platform-scale BI solutions.

Design, maintain, and automate GTM business data models, ensure data quality and observability, build BI-as-code pipelines (CI/CD, Git), create visualizations, and partner with Sales, Marketing, Finance, and Product to enable reliable reporting, analytics, and AI capabilities.

Build governed gold-layer data models and a single-source metrics layer in Snowflake (dbt); create and optimize dashboards in enterprise BI tools; use AI coding agents and AI-assisted tooling to accelerate development; ensure data quality, governance, and consistency; collaborate with data engineering and stakeholders to deliver trusted analytics for internal and client-facing use.

Analyze healthcare and operational datasets to create, validate, and maintain reports and dashboards using SQL, Excel, and BI tools. Support utilization, cost containment, regulatory reporting, and ad hoc analyses. Collaborate with stakeholders to define requirements, document workflows, and deliver actionable recommendations.

Architect and scale a governed BI and analytics platform (Snowflake, dbt, Sigma) to deliver trusted, standardized KPI frameworks and semantic layers. Build high-quality data models, optimize SQL for large datasets, enable self-serve analytics, mentor engineers, drive governance and testing standards, and partner with Product, Data Science, Finance, and business teams. Promote AI-assisted tooling to accelerate analytics delivery and improve metric trust and reporting consistency.

Validate and QA data across UI and API sources, investigate issues, manage taxonomy mismatches, compile non-automated reports, and update/maintain dashboards (Power BI/Tableau). Collaborate with Business Strategy, Investment, and Analytics teams to resolve data and KPI anomalies.