Top Senior Data & Analytics Jobs in Los Angeles, CA

Develops dashboards, reports, KPIs, data models, and API-driven pipelines using Tableau, Power BI, SQL, Smartsheet, and related tools. Collects and validates data, analyzes trends, supports PMO reporting and maturity assessments, improves reporting automation and data quality, and provides insights for program reviews and leadership decisions. The role also supports project tracking and runs Change Board Meetings.

Build Vast’s People Analytics function from the ground up, including data governance, a unified People data model, trusted metrics, executive Tableau dashboards, and workforce analytics. Develop attrition, retention, performance, compensation, pay equity, and headcount models; evaluate People programs; and provide actionable recommendations to senior leaders. The role also establishes self-service reporting, privacy standards, analytics processes, and the roadmap for scaling the function and team.

Leads applied AI and health data architecture initiatives for payer clients. Designs cloud-native platforms, pipelines, data models, integrations, and modernization roadmaps across AWS, Azure, Databricks, and Snowflake. Oversees data quality, governance, anonymization, performance optimization, and legacy migrations while advising stakeholders on AI-ready architectures. Manages multi-team delivery, resolves technical issues, presents solution tradeoffs, and coaches practitioners.

Build and operate production data pipelines, models, and data products supporting finance, accounting, treasury, compliance, and regulatory reporting. Partner cross-functionally to define requirements, model on-chain and internal data, and ensure data reliability through reconciliation, quality checks, monitoring, and alerting. Use SQL, Python, cloud data warehouse, Airflow, dbt, and AI tooling. Mentor engineers, review technical work, document systems, and communicate data concepts to technical and non-technical audiences.

Lead business intelligence initiatives supporting Snapchat’s Sales organization. Analyze data from multiple sources, identify campaign and industry trends, build dashboards and reports, deliver actionable revenue insights, and recommend optimization strategies. Partner with cross-functional teams on measurement strategies, product feedback, revenue programs, and growth initiatives. Communicate complex analyses to technical and non-technical audiences and influence business decisions through compelling data stories.

Design, build, and own scalable ETL/ELT pipelines, data models, and data infrastructure. Improve data quality, observability, performance, and CI/CD for data workflows. Partner with analytics, ML, software, and product teams, mentor engineers, and resolve complex data issues.

The Data Scientist in Finance will analyze financial data, create dashboards, collaborate on data engineering, and find improvements for the business.

Build and maintain production data pipelines, dbt models, Airflow workflows, and governed datasets supporting People Analytics. Integrate Workday and other HR systems into reliable Snowflake data products, implement data quality monitoring, row-level security, semantic models, and AI agents. Partner with engineers, analysts, data scientists, and business stakeholders to deliver trusted data solutions, communicate technical trade-offs, enforce governance, and mentor other engineers.

Principal Data Analyst responsible for driving data-informed business strategy, leading end-to-end analysis, and building analytics foundations for a new product. The role includes designing data capture and pipelines, creating reporting-ready datasets, supporting governance and privacy, conducting statistical analysis, segmenting clients, partnering with product and engineering, communicating insights to executives, and mentoring analysts. The analyst will also use AI to improve effectiveness and establish reliable data sources.

Own the people analytics roadmap, build reliable HR data pipelines and reporting, and deliver workforce, talent, and process insights. Analyze employee lifecycle operations, measure performance, identify automation opportunities, and develop dashboards and predictive analyses for senior leaders. Partner across People, HRIS, IT, Finance, Legal, and data teams to improve data governance, privacy, operational efficiency, and employee experience. Establish analytical standards and coach People colleagues on data-driven decision-making.