Top Business Intelligence Jobs in Los Angeles, CA

Analyzes data from multiple sources to identify business and advertising performance trends, build dashboards and reports, and deliver actionable recommendations. Partners with account management and cross-functional teams on measurement strategies, product insights, campaign optimization, and revenue-impacting initiatives. Communicates complex analytical findings to technical and non-technical audiences and influences business decisions through data storytelling.

Leads business intelligence and analytics engineering initiatives for Snap’s People Team. Designs scalable data pipelines, models, data products, dashboards, and self-service analytics solutions. Translates business needs into technical requirements, conducts statistical analysis, improves data quality and operational reliability, and delivers actionable insights. Owns systems end to end while mentoring team members and communicating effectively with executives, business partners, analysts, and technical teams.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

Lead CX data intelligence initiatives using SQL, dashboards, analytical models, and AI/LLM techniques. Analyze customer journeys, operational metrics, churn risks, and retention indicators; develop insight agents and self-service reporting; define CX health metrics; and translate findings into strategic recommendations, process improvements, and experiments. Partner with operations, support, product, data, and engineering teams while maintaining data quality, governance, and documentation.

Leads business intelligence, reporting, analytics, and project delivery initiatives. Partners with stakeholders and technical teams to gather requirements, define reporting solutions, manage timelines and risks, validate data and outputs, maintain dashboards, support testing and implementation, and identify process improvements. Uses complex data analysis, business process evaluation, and reporting expertise to improve operational performance, leadership decision-making, governance, automation, and consumer experiences.

The BI Analyst develops dashboards, reports, and visualizations; gathers business requirements; performs ETL and SQL-based data analysis; ensures data quality and governance; identifies trends and anomalies; provides recommendations; and trains users on BI tools and reports.

Develops self-service BI tools, data sources, data marts, and interactive visualizations using Tableau or Power BI. Partners with clinical and operational leaders to translate information needs into actionable insights. Combines data from warehouses, lakes, and external sources; supports ETL, validation, data governance, platform maintenance, security access, and compliance. Trains and mentors analytics team members while ensuring BI assets are accurate, trusted, secure, and effectively maintained.

Build and maintain reporting suites, dashboards, analytical models, and quantitative analyses that support business decisions. Partner with leaders across Operations, Risk, Servicing, Finance, Product, and Sales to investigate complex questions, generate actionable insights, and identify growth opportunities. Collaborate with data engineers to ensure accurate data delivery while managing multiple cross-functional projects and communicating findings through clear, persuasive narratives.

Build and maintain Tableau dashboards, KPIs, reports, forecasts, and business analyses for Customer Success, Marketing, and Sales. Query and validate cloud warehouse data using SQL, partner with Analytics Engineering on data models and quality, and translate stakeholder questions into actionable insights. Support self-service analytics, AI-enabled tools, documentation, training, and governance while analyzing pipeline, campaign performance, retention, churn, revenue, and customer data.

The Epic Business Intelligence Developer creates analytics content for Epic data, configures applications, writes SQL reports, and manages data models and analytics catalogs.

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.

Leads business intelligence and database analysis to generate revenue insights, solve complex business problems, optimize digital performance, support sales and marketing initiatives, and develop predictive data products. The role requires advanced SQL analysis across large data warehouses, Tableau and web analytics reporting, data validation, executive presentations, and leadership of junior staff.

Build and maintain business intelligence models, dashboards, reports, and compensation analyses for shelter, breeder, and sales channels. Support insurance regulatory reporting, ad hoc analytics, data quality, governance, automation, and performance tuning. Partner with data engineering, compliance, and business teams to improve enterprise data models and enable AI-driven initiatives.

Develop and optimize SQL Server and SSIS billing pipelines, automate data movement and validation with Python, and use R and Python for analytics, anomaly detection, and billing decision models. Build data-quality frameworks, support internal reporting tools, integrate ERP APIs, and collaborate with finance and operations stakeholders. The role requires maintainable, tested, auditable solutions and ownership of features across databases, pipelines, analytics, and internal applications.

Lead business intelligence strategy across product, clinical, commercial, finance, and engineering teams. Build measurement frameworks, semantic layers, reporting solutions, and visualizations that demonstrate business value and support data-informed decisions. Own the data lifecycle from ideation through client-facing delivery, ensure data governance and integrity, and translate complex datasets into actionable insights. Collaborate on scalable data architecture and apply statistical methods, advanced analytics, and emerging AI-driven BI capabilities.

Develop and maintain Amazon QuickSight dashboards in a secure CMS environment supporting healthcare quality improvement programs. Responsibilities include gathering requirements, creating analyses and visualizations, validating data and calculations, documenting dashboards, conducting user acceptance testing, troubleshooting, and supporting deployment. The role also develops Tableau visualizations, performs ad hoc analysis, coordinates with stakeholders, and communicates technical findings and dashboard guidance.

Supports enterprise data governance and business intelligence initiatives by profiling datasets, defining quality rules, validating metadata and lineage, maintaining business glossaries, and testing API integrations. Develops data-quality scorecards, governance reports, dashboards, documentation, and training materials. Collaborates with data owners, stewards, engineers, and government stakeholders while tracking remediation and testing evidence in Azure DevOps. The role requires Power BI, data governance, data-quality, SQL, ETL, and relational database experience in a Navy environment.

Design and implement scalable BI data systems, models, and AI-powered tooling. Translate business questions into reliable datasets, optimize warehouses and queries, apply software engineering practices, partner with product and engineering teams, and mentor teammates. Process large-scale data using modern cloud platforms and technologies such as Spark, Databricks, and Kubernetes.

Develop and maintain BI reports and dashboards for the Mortgage Lending Division. Analyze large datasets, identify trends, validate reportable data, and support regulatory reporting such as HMDA and Fair Lending Analysis. Collaborate with business teams to gather requirements, automate reporting processes, document data definitions, and provide training on reporting tools. The role also supports data dictionaries, exception reporting, and operational improvements.

Develop and maintain Power BI, SSRS, SQL, recurring, and ad hoc reports for the Mortgage Lending Division. Analyze large datasets, validate regulatory reporting data, identify trends, automate reporting, and provide actionable insights. Collaborate with business units, support HMDA and fair lending reporting, document data dictionaries and procedures, and train users on reporting tools.

Leads a client’s migration from SQL Server, SSIS, and SSRS to Snowflake and Sigma while maintaining legacy reporting operations. Designs data models, ETL pipelines, reports, dashboards, source-to-target mappings, and migration plans; validates reporting parity and coordinates phased cutovers. The role also provides client-facing technical leadership, troubleshooting, documentation, peer reviews, and ongoing support for banking data and reporting systems.

Lead ownership of BI reporting infrastructure: build and standardize dashboards, extract insights from messy third‑party data, partner with marketing teams to drive performance optimization and deliver proactive retrospective analyses that influence business decisions.

Develop business intelligence and revenue reporting tools, automate Finance reporting processes, perform ad hoc and quantitative analyses, and translate complex data into actionable insights. The analyst will support company initiatives, present findings to technical and non-technical stakeholders, and provide decision-making guidance across the organization.

Develops and maintains Power BI dashboards and data models, defines KPIs with stakeholders, validates data accuracy, and collaborates with Data Engineering on optimized analytical models. The role documents data lineage and reporting assumptions, supports self-service BI through communications and training, and automates manual reporting processes. It requires SQL, Power BI, DAX, Power Query, data modeling, and data warehouse knowledge, plus strong communication and cross-functional collaboration skills.

Leads enterprise business intelligence and analytics across multiple divisions and locations. Establishes governed KPI definitions, reporting architecture, financial and operational analytics, semantic models, data-quality practices, and self-service reporting. Partners with FP&A, IT, Finance, and Operations to align analytics with financial results, guide technical delivery, evaluate BI platforms, and support forecasting and performance improvement. Directs internal or external development teams and communicates actionable insights to executives and operating leaders.