Top Remote Analytics Engineer Jobs

As a Staff Analytics Engineer, you'll lead analytics architecture, ensure data quality, collaborate with stakeholders, and drive AI-powered data insights for business decision-making.

As a Lead Analytics Engineer, you will build data products, collaborate with stakeholders, drive technical excellence, and mentor junior engineers.

Develop and productionize safety and performance metrics for autonomous driving by analyzing large-scale vehicle, simulation, and external data. Build scalable data pipelines, interactive visualizations, and analytics infrastructure to support safety assessment, monitoring, investigations, and stakeholder decision-making. Apply engineering judgment, signal processing, and statistics to derive analysis-ready features and evidence for launch readiness.

Design, develop, and secure database systems that integrate structured and unstructured data from diverse sources. Build ETL processes, SQL/PLSQL/T-SQL routines, Oracle APEX web apps, and Power BI reporting to enable data mining, quality checks, and analytics for engineering and materials data.

The role involves gathering requirements for BI and data projects, providing documentation and support, and analyzing data to facilitate decision making and system improvements. The candidate will liaise between business units and IT, support application deployments, and drive transformation projects.

The AV Safety Engineering Analytics Engineer develops data analytics infrastructures, defines metrics for safety assurance, and creates visualizations for automated vehicle technologies, enhancing decision-making through data integration and analysis.

The Staff Analytics Engineer will own the Financial Subledger Data Platform, build dbt models, implement data quality controls, and mentor a junior engineer, ensuring high operational reliability and cross-functional collaboration.

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.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.

Build and own the reporting and insight layer: write optimized Redshift queries, build dashboards, monitor model feedback signals, triage and prioritize investigations for data science, maintain ETL pipelines ingesting semi-structured data, and enable Customer Success with clear metrics and onboarding checks. Move into model validation and automation to scale analytic workflows.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

The Senior Data Analytics Engineer analyzes and delivers business intelligence solutions, builds data pipelines, and collaborates with clients to meet their data-driven needs.

The Staff Product Analytics Engineer will enhance product data usage across teams by owning data infrastructure, creating tools for self-service data, and ensuring data-driven decisions. Responsibilities include collaborating with various teams to improve data insights and maintain data pipelines.

Lead Analytics Engineer responsible for end-to-end data solution design, evolving data architecture, mentoring engineers, driving data health and observability, enabling cross-functional measurement, and contributing to roadmap and decision-making.

Design, build, and operate production-grade AI tools, automations, and integrations for HR workflows. Lead LLM-based solutions (prompting, RAG), integrate people systems (Workday, Slack, Google Suite), improve data quality, support end users, and drive measurable productivity and product roadmap decisions.

As a Billing & Analytics Software Engineer, you'll design and maintain the billing pipeline, integrate billing systems, and develop customer-facing analytics dashboards to support revenue recognition and operational observability.

Design, build, and maintain scalable analytics data models and pipelines in AWS/Redshift. Collaborate with data engineering and business stakeholders to translate requirements, support BI dashboards, enforce schema and naming standards, maintain documentation and metrics, ensure data quality with tests and alerts, and promote best practices like version control and code reviews.

Own and build reliable analytics data products: define metrics, create and maintain dbt models, design dashboards for growth/finance/ops, improve data quality via testing and monitoring, and enable self-serve analytics for stakeholders.

The Engineer will develop data analytics infrastructure for AV safety analytics, integrate simulation data, and collaborate to enhance automated driving systems' validation and performance metrics.

The AI/ML Engineer will focus on integrating AI/ML methods into safety assurance analytics for autonomous vehicles, develop data infrastructure, and collaborate across teams to improve vehicle safety performance using large-scale data analysis.

Own and improve the dbt modeling and semantic layers, implement CI/CD, tests, observability, and governance; build governed metrics for BI and AI consumption; partner with Data Engineering and Risk to stabilize pipelines and improve data quality and documentation.

The Analytics Engineer will design and implement analytics solutions, maintain reporting dashboards, partner with Product on KPIs, and support marketing with analytics.

The Lead GTM Analytics Engineer designs and manages the data model for GTM execution, ensuring accurate metrics and insights across Sales, Marketing, Customer Success, and Partnerships to drive revenue performance.

As a Senior Analytics Engineer, you'll build data pipelines and dashboards, partner with stakeholders for KPI development, and ensure data quality across the company.

The role involves building and maintaining data pipelines, optimizing data warehouses, creating analytics dashboards, and implementing predictive models to enhance revenue operations.