Top Remote Data & Analytics Jobs in San Diego, CA

Own advanced analytics for Airbnb product teams, using large datasets, statistical modeling, experimentation, causal methods, forecasting, and metrics development to guide product and business decisions. Build reporting and analytical tools, collaborate cross-functionally, automate repetitive work with AI, and present actionable insights to senior stakeholders. The role supports Guest App or API initiatives, including promotions and marketplace optimization.

Conduct product analytics for MoneyGram’s digital money transfer products. Analyze customer behavior, product performance, experiments, feature releases, and cohort metrics to guide product strategy and growth. Build insights and reporting, collaborate with Product, Engineering, Marketing, Finance, and international teams, and improve analytics platforms, automation, and visualization processes. Translate complex findings into actionable recommendations for technical and non-technical stakeholders.

Leads enterprise Business Intelligence strategy, architecture, governance, security, and self-service analytics adoption. Architects solutions across Power BI, Tableau, SAP BusinessObjects, and Databricks; establishes semantic models, data standards, DevOps, CI/CD, and reporting performance practices. Partners with executives and technical teams to modernize analytics platforms, reduce manual reporting, and enable AI-ready decision-making. Mentors BI professionals and drives enterprise data literacy and analytics transformation.

Leads commercial analytics and business intelligence strategy, including executive dashboards, account reporting, revenue and pricing analytics, operational KPIs, forecasting, segmentation, and predictive modeling. Partners with Sales, Finance, Marketing, Operations, and Product to improve revenue, profitability, customer retention, and marketplace performance. Presents insights to executives and customers while managing analytics teams, budgets, vendors, and BI scalability.

Leads the strategy, architecture, and delivery of an advertiser intelligence platform. Defines canonical data models, golden advertiser profiles, ingestion and identity resolution, AI/ML enrichment, predictive analytics, vector matching, governance, and business workflow integrations. Partners with engineering, product, sales, customer success, operations, finance, and executive stakeholders to deliver scalable, trusted data capabilities and measurable revenue, retention, and decision-making improvements.

The Business Intelligence Analyst queries cloud data, builds dashboards and recurring reports, validates data integrity, and delivers actionable insights to business leaders. The role embeds AI tools into reporting, documents data definitions and processes, automates manual work, and partners with FP&A, Business Operations, and Data Engineering. It requires SQL, Excel, BI reporting experience, and practical AI application, with Python, R, Git, and dbt listed as preferred skills.

Owns B2B and B2C funnel, enrollment, revenue, and marketing performance reporting. Builds executive and Board dashboards, analyzes CAC, LTV, retention, conversion, spend efficiency, and ROI, and reconciles marketing activity with financial results. Maintains KPI definitions and reporting governance while partnering with Marketing, Finance, FP&A, Sales Operations, and Data teams. Supports strategic planning, diligence requests, and actionable business recommendations through accurate, cross-functional analytics.

Define and lead enterprise data architecture centered on Snowflake, including source integration, ingestion frameworks, data modeling, governance, security, compliance, quality, lineage, and AI-ready data products. Build reference pipelines using AWS and Snowflake services, establish engineering standards, optimize performance and costs, and guide architecture decisions. Partner with analytics and AI teams, lead reviews, mentor engineers, and influence stakeholders across the organization.

Designs, builds, and maintains Snowflake-based enterprise data warehouse solutions, including data architecture, ETL/ELT pipelines, security, deployment, data quality, modeling, and performance optimization. Partners with integration, analytics, governance, business intelligence, and architecture teams. Supports production operations, resolves ingestion and transformation issues, develops AWS-to-Snowflake scripts, documents implementations, and translates business requirements into scalable data solutions.

Leads market research and insights partnerships across operating groups, shaping research agendas and translating qualitative and quantitative findings into strategic recommendations. Manages and develops insights analysts in a matrixed environment, allocates resources across portfolios, oversees research quality and methodology, and presents actionable findings to executive stakeholders. Requires advanced research, statistical analysis, survey design, storytelling, stakeholder influence, and project management expertise.

Supports PMI’s research agenda through survey, qualitative, secondary, quantitative, business analysis, and foresight research. Analyzes AI, technology disruption, macroeconomic, industry, and future-of-work trends; translates complex findings into executive-ready insights, narratives, thought leadership, and strategic recommendations. The role requires rigorous methodology, independent initiative, cross-functional collaboration, strong communication, and the ability to assess technical developments and their business implications.

Designs, develops, and maintains scalable ETL/ELT pipelines and data platform capabilities for high-volume healthcare data. Responsibilities include complex SQL development, Airflow orchestration, dbt transformations, data quality frameworks, pipeline monitoring, troubleshooting, performance optimization, and documentation. The role collaborates with Data Operations, Product, Analytics, Data Science, and clinical teams to deliver reliable data for analytics, reporting, product features, and AI/ML initiatives.

Design, develop, and maintain scalable ETL/ELT data integration pipelines supporting analytics, reporting, and product capabilities. Build ingestion, transformation, validation, and curated data layers; optimize production workflows; document systems; and implement data quality monitoring and testing. Collaborate with implementation, engineering, analytics, and customer success teams to resolve data issues, support onboarding, and ensure reliable, accessible data.