Top Hybrid Data & Analytics Jobs in Los Angeles, CA

Supports data analysis projects in PwC’s Advisory practice, researching datasets, identifying patterns, integrating data, and creating dashboards and visualizations with Alteryx and Power BI. Assists with algorithm development, analytics automation, and data-driven insights for clients. The internship emphasizes learning PwC methodologies, collaborating with experienced professionals, and gaining exposure to AI, cloud platform design, and data architecture.

Leads third-party advertising measurement strategy, partner governance, benchmarking, meta-analyses, and analytics innovation. Advises senior executives, influences cross-functional roadmaps, develops measurement playbooks, presents industry thought leadership, and builds measurement capabilities across Sales, Product, Marketing, and Partnerships. The role requires advanced statistical and causal inference expertise, hands-on SQL and visualization skills, and more than ten years of advanced analytics and measurement experience.

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.

Lead product data analytics: analyze large datasets, build models and dashboards, design and evaluate A/B tests, advise product decisions, automate analytics with AI-enabled tools, and collaborate with global R&D and product teams to deliver actionable insights.

Develop and maintain scalable dbt models, dimensional data models, semantic layers, metrics, documentation, tests, and data governance on Snowflake and modern data platforms. Partner with cross-functional stakeholders to define KPIs and deliver trusted self-service analytics. Investigate data quality issues, optimize workloads, improve platform reliability, mentor junior team members, and explore AI-driven workflow automation.

Govern taxonomy, naming standards, UTM frameworks, and data quality across media, analytics, engineering, vendors, and clients. Implement and QA tracking across GA4, CM360, DV360, and related platforms; troubleshoot reporting discrepancies; document root causes and resolutions; support marketing technology integrations and proof-of-concept initiatives; develop AI automation; and communicate technical processes and recommendations to client and executive stakeholders.

Own and evolve the end-to-end product analytics platform, including instrumentation, event collection, ingestion, raw data storage, data pipelines, analytical models, metrics, dashboards, quality monitoring, observability, lineage, and governance. Partner with software engineers to ensure analytics data is accurate, scalable, traceable, and reliable for business and product decision-making.

Analyze survey and secondary data using statistical and multivariate techniques. Clean, structure, code, and summarize datasets; use SPSS, R, Excel, Python, and VBA to conduct analyses and automate procedures. Prepare Excel outputs and PowerPoint presentations, explain findings to internal and external clients, support analytic planning, and ensure accurate, timely delivery of market research work.

Lead A+E's first-party customer data strategy and Analytics Engineering to build a composable CDP and identity infrastructure. Define audience use cases, activation pipelines into Iterable/Adobe, ROI/KPI frameworks, and integrate owned signals with paid media measurement. Partner cross-functionally to embed first-party data into marketing, product, and revenue decisions while ensuring privacy and scalable data governance.

As a Senior Data Engineer, you will design and operate data transformation pipelines, workflows, and AI-assisted data visualization tools, collaborating with an experienced team.