Analytics Engineer jobs in Los Angeles, CA

The Analytics and Insights Engineer III designs and executes analyses to address client business questions across paid, owned, and earned channels. They are responsible for developing measurement frameworks, performance reporting, and deploying experimentation strategies using various data tools.

The Senior Analytics Engineer will lead cross-functional analytical initiatives and build automated reporting and AI-driven insight tools. They will also manage the development of knowledge repositories and logic for AI chat agents to support business decision-making.

Process and analyze raw aircraft data to identify system malfunctions and ensure the health of C-17 avionics and mission systems. Develop efficient algorithms for data mining and provide technical recommendations to customers regarding aircraft performance and design non-conformances.

The Implementation Engineer designs and documents measurement plans while implementing tags, data layers, and tracking across client websites and applications. They also troubleshoot data collection, validate event flows into enterprise CDPs, and collaborate with marketing and engineering teams to ensure accurate data activation.

Design and implement high-quality features for Apple's video applications, addressing complex technical challenges across iOS and macOS. Collaborate with engineers across teams to advance professional video editing capabilities and deliver features for creative professionals.

Build and improve the data platform, integrating advertising APIs and operational sources into reliable pipelines, Snowflake models, documented metrics, and Power BI reporting. Investigate data and pipeline issues, improve observability and performance, and develop datasets and feedback loops that connect ad performance with creative decisions and analytics or machine learning applications.

The Data & Analytics Engineer will own and maintain the data platform infrastructure while connecting the data warehouse to AI, finance, and business teams. They will build reliable data pipelines, develop dbt models, and create dashboards to support cross-functional business KPIs and predictive modeling.

You will own end-to-end data domains, including modeling, definition, and reliability for critical business datasets. You will also mentor team members, drive technical standards, and lead the migration of reporting to curated models.

The Senior Business Analytics Engineer will own analytics and reporting for ticketing and other business verticals by designing and maintaining BI dashboards. They will also conduct deep-dive analyses to provide actionable recommendations and ensure data integrity across source systems.

You will own global DTC subscriber forecasts by building data pipelines and collaborating with data science and engineering teams. Additionally, you will diagnose forecast variances and partner with stakeholders to improve dashboarding environments.

Design and optimize robust ETL/ELT pipelines to integrate diverse HR data into a scalable analytics platform. Develop and govern secure data models to provide actionable insights for the employee lifecycle.

Design and maintain scalable batch and real-time data pipelines to enable self-service analytics and AI applications. Develop governed data products, semantic layers, and metrics frameworks to support BI and machine learning use cases.

Provide senior technical leadership for Analytics Engineering, shaping data foundations, modeling standards, architecture, governance, quality, tooling, and developer experience. Build trusted canonical datasets, semantic layers, and AI-enabled analytical tools that support self-service analytics and improve decision-making across the company.

Own canonical data models and KPI definitions for payments, billing, subscriptions, identity, and Trust & Safety across Scribd, Everand, and Fable. Improve data quality, observability, and lineage; build AI tools on certified data; and set technical standards while influencing partners and mentoring colleagues.

Support nationwide deployment of a case management platform used for docketing, scheduling, case tracking, and caseload reporting. Train legal and administrative users, provide deployment support, troubleshoot issues, and develop documentation and knowledge resources.

The Data Engineer II designs and builds reliable, scalable ELT pipelines to support analytics, reporting, and AI/ML applications. They also partner with cross-functional teams to translate business requirements into robust data models and maintain data governance standards.

You will design and maintain services to process financial data while collaborating with cross-functional teams to ensure accurate settlement and reporting. Additionally, you will build full-cycle analyses, develop real-time dashboards, and automate reconciliation processes to support financial operations.