Top Remote Analytics Engineer Jobs

The Analytics Engineer will manage BI modeling, create dashboards, ensure data quality, and collaborate with customers and teams for reporting needs.

As a Staff Analytics Engineer, you will bridge data engineering, data science, and business analytics to generate actionable insights, build data models, and empower stakeholders across the organization.

Design, build, and operationalize cloud-based data pipelines and transform raw data into analysis-ready datasets. Collaborate with business, analytics, and engineering teams to develop data models, automate data preparation, and document transformations. Support Power BI models and dashboards, improve data accessibility and reliability, and mentor peers while exploring new data technologies and automation techniques.

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.

As an Analytics Engineer, you will design and maintain SQL models for on-chain data, work with transformation tools, and collaborate with engineers on data pipelines.

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 Senior Analytics Engineer will design scalable data models, collaborate with teams to create analytics pipelines, and implement data governance best practices.

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.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

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).

The Analytics Engineer will build data models and pipelines, ensure data quality, and enable self-service analytics across the organization.

The Analytics Engineer will develop and manage dbt models and SQL queries, collaborate with stakeholders, ensure data quality, and support data analysis. They'll translate business needs into technical data solutions and maintain clear communication with diverse teams.

As a Senior Data & Analytics Engineer, you'll lead data initiatives, manage a team, and ensure data quality while turning insights into actionable decisions across the company.

The Analytics Engineer will own and optimize the DBT analytics pipeline, enhance data models, ensure data accuracy, and innovate solutions while collaborating with stakeholders.

The Senior Analytics Engineer collaborates with product managers and data teams to develop analysis tools, metrics, and frameworks that enhance media production efficiency and strategy at Netflix.

Architect, build, and maintain scalable ELT data pipelines and analytics-ready data marts. Lead dbt modeling, ensure data quality, CI/CD, and documentation. Partner with stakeholders, mentor junior engineers, evaluate tooling (reverse ETL), and drive long-term data platform strategy.