Top Senior Business Intelligence Jobs in Los Angeles, CA

Leads the Business Intelligence and Revenue Analytics function, balancing team management with hands-on analysis. Develops dashboards, KPI frameworks, forecasts, and reporting for Sales, Marketing, Revenue Operations, and executives. Partners with Data Engineering on data models, pipelines, governance, and quality. Translates business needs into analytical solutions, delivers actionable insights, manages the analytics roadmap, prioritizes initiatives, and coaches a small team.

Designs and maintains BI solutions, writes optimized SQL and stored procedures, and builds AI-assisted reports and dashboards using Power BI, Tableau, and Excel. Translates business questions into actionable insights for Sales and cross-functional teams, develops data models, supports reporting migrations, and ensures data quality, governance, documentation, and consistency across platforms.

Own and enhance Sigma dashboards and business intelligence reporting for the Records Retrieval business. Partner with stakeholders to translate business needs into scalable data solutions, analyze complex datasets, improve data quality and governance, define reporting standards, and support Snowflake data warehouse and modeling initiatives. Deliver actionable insights, automate reporting processes, evaluate analytics tools, and independently drive analytics projects from requirements through delivery.

The Sr. Business Intelligence Engineer leads BI development, governs Power BI architecture, mentors developers, and ensures reliable reporting and documentation, while managing metrics and improving automation.

Lead a BI engineering team, overseeing dashboards, data models, SQL/dbt transformations, ETL pipelines, Airflow DAGs, data warehouses, CI/CD, governance, and quality standards. Partner with stakeholders to define reporting requirements, conduct advanced analyses, manage Agile projects, and develop data strategy. Mentor team members and support production deployments. This fully remote role requires travel to Denver for five business days each quarter.

Transforms complex retail and consumer data into business-ready datasets, scalable pipelines, reporting solutions, automation, and client deliverables. Designs data integration solutions in Unify, troubleshoots connector issues, explores AI-driven improvements, and partners with Product, Engineering, Client Development, Operations, and business stakeholders to define requirements and deliver scalable solutions.

The BI Manager leads data analytics by managing a BI team, collaborating with stakeholders, overseeing data architecture, and enhancing reporting processes.

Develop Power BI dashboards, reports, data models, and analytical tools for federal consulting engagements. Gather stakeholder requirements, integrate and validate operational data, create DAX calculations and Power Query transformations, and support forecasting, staffing, cost, inventory, and performance analysis. Optimize and document solutions, conduct testing and training, and transfer knowledge to Government users. Collaborate with logistics, operations research, security, and project management stakeholders.

The Market & Business Intelligence Manager will lead analytics strategies, manage a team of business analysts, and provide insights to support firm strategy and decision-making.

The Business Intelligence / Data Analyst will optimize the data reporting pipeline using Google Big Query and Omni, work with product management, implement reports, and conduct ongoing maintenance.

Lead a team of six analysts to own BI strategy, data governance, reporting roadmap, and automation. Build dashboards, self-service analytics, and cloud data pipelines (Databricks/Snowflake). Partner with Sales, Talent, and Operations to define KPIs, improve data quality, streamline systems, and deliver actionable sales and operational insights.

Lead development and implementation of finance analytics and COGS reporting. Build scalable data solutions, cost models, and dashboards; collaborate cross-functionally with finance, production, supply chain, and engineering to improve cost visibility, processes, and decision-making. Own end-to-end BI deliverables and influence adoption of robust cost data and analytics.

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.

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.

Design, build, and maintain enterprise Power BI dashboards and data models. Integrate multiple data sources, write DAX, ensure data quality and performance, support stakeholders with requirements, documentation, governance, and ad hoc analytics to enable operational and executive decision-making.

The BI Analyst will manage customer relationships within a business group to deliver reporting and analytics solutions, requiring strong communication and analytical skills.

Lead analytics and BI for Digital Product Operations: define product and adoption metrics, build dashboards, ensure data governance and quality, measure ProdOps effectiveness, coach PM/POs, diagnose adoption gaps, and drive interventions that improve product planning and delivery.

Own and maintain KPI reporting pipelines and business logic, ensure data quality, diagnose KPI changes, perform deep-dive analyses, build dashboards and visualizations, architect data models and curated reporting zones, and partner with Data Engineering and product/marketing stakeholders to enable self-service analytics.

Lead business intelligence efforts to analyze complex data, define KPIs, identify operational inefficiencies, and recommend process improvements. Collaborate with cross-functional teams and executives to implement data-driven strategies, manage improvement projects, monitor resource allocation, and ensure compliance with policies and regulations.

Lead product analytics efforts to define KPIs, build measurement frameworks, analyze customer behavior, and generate insights that influence product and engineering decisions. Partner with Product, Engineering, and Data teams to design event tracking, run experiments, quantify opportunity sizes, and communicate recommendations through clear narratives and visualizations to drive product adoption, retention, and business outcomes.

Lead BI developer owning end-to-end reporting for performance marketing verticals. Build and standardize dashboards, author LookML models, extract insights from messy third-party data, partner with Yield/Paid Media/Account teams, deliver retrospective analyses, and drive adoption and business impact.

Lead BI Developer owns reporting infrastructure end-to-end, building standardized, trusted dashboards and LookML models, analyzing messy third-party data, partnering with Yield/Paid Media/Account teams to deliver actionable performance marketing insights and retrospective analyses that drive business decisions.

Lead the architecture and development of CareDx's enterprise BI ecosystem. Own Power BI modeling, DAX optimization, governance (RLS, deployment pipelines), and self-service enablement. Collaborate with data engineering to build scalable Databricks/Delta Lake/PySpark pipelines, leverage Microsoft Fabric and Lakehouse architecture, mentor BI developers, translate business needs into analytics solutions, and drive BI performance and reliability.