Top Remote Analytics Engineer Jobs

As an Analytics Engineer, you'll manage the data stack, design database architecture, build data pipelines, and oversee reporting and data quality.

As a Payment Analytics Engineer, you will ensure data consistency in payments, automate reporting, analyze interchange data, and collaborate with Engineering for data management.

In this role, you will enhance analytics workflows, mentor peers, drive data product improvements, and use AI tools for automation in Corporate Finance.

The Integrated Risk Analytics Developer leads analytics initiatives, designs Power BI solutions, and integrates data to support risk management and decision-making.

Lead the development of programmatic signals analytics for Netflix Ads, creating metrics and dashboards for optimizing audience targeting and ROI.

Lead the architecture and development of data ecosystems and analytics capabilities, optimizing data products for customer insights and decision-making.

Collaborate with stakeholders to analyze data and metrics, implement analytical models, and enhance data quality for business forecasting.

The Analytics Engineer will build analytical frameworks to enhance identity experiences at Netflix, collaborating across teams to ensure data quality and drive insights.

As a Staff Product Analytics Engineer, you will build and maintain data infrastructure, collaborate across teams to enhance product data use, and develop tools for data self-service.

The Analytics Engineer will enhance BI infrastructure, collaborate with Data Engineering, and deliver analytics-ready data. Responsibilities include managing Snowflake, dbt projects, and CI/CD workflows, optimizing data structures, and supporting BI initiatives.

As an Analytics Engineer, you will build data workflows and analytics products, ensuring data accuracy and reliability while contributing to financial data deliveries.

The role involves designing and maintaining ETL pipelines, data models, ensuring data quality, and collaborating with teams to drive data-driven decisions.

The Enterprise Performance Analytics Engineer builds and maintains data pipelines and models, ensuring data quality and efficient reporting for analytics teams.

The Senior Analytics Engineer role involves designing data models, optimizing data pipelines, collaborating with teams, and translating business requirements into actionable insights, driving commercial value from data.

The Principal Systems Development & Analytics Engineer leads the design and operation of automation systems, ensuring reliability and integration across data sources. They define architecture, enforce system controls, and optimize operational analytics while mentoring other engineers.

The Lead Analytics Engineer will model revenue, specifically subscription revenue, manage financial KPIs, and ensure reconciliation with source systems like Stripe, while adhering to data governance standards.

The Detection Engineer will enhance OT security by cataloging assets, developing detection logic, troubleshooting configurations, and conducting research on PCAPs in collaboration with engineering teams.

The Senior Data & Analytics Engineer will design and maintain data pipelines, develop analytics schemas, build visualizations, and perform deep-dive analyses to drive business decisions.

The Analytics Engineer will design datasets, metrics, and dashboards for the Ads business, conduct analyses, and drive projects to solve business problems.

As a Business Intelligence and Analytics Engineer, you will develop data tools, ensure data quality, deliver analytical insights, and collaborate with cross-functional teams to empower data-driven decision-making.

Lead end-to-end web and mobile analytics: design and implement tagging strategies, ensure data quality, build data pipelines and dashboards, analyze user behavior, and provide actionable insights to Product, Marketing, and Engineering stakeholders.

Lead the development of scalable analytics solutions for content distribution, create metrics and dashboards, and collaborate with cross-functional partners.

The Staff Analytics Engineer is responsible for defining, modeling, and governing the enterprise data layer, ensuring accurate and auditable reporting across the organization. Key tasks include managing data contracts, enforcing data quality standards, and collaborating with multiple teams to maintain a consistent data model.

The Manufacturing Analytics Engineer will manage the analytics pipeline, transforming operational data from OT systems into actionable insights for decision-making, while collaborating with Engineering, IT, and Operations.

Design, build, and maintain the analytics layer and data models using Data Vault methodology. Develop ETL pipelines, optimize data warehouse performance and cost, collaborate with stakeholders, and support BI and data science consumption (DBT, Snowflake, Tableau/Power BI).