Top Remote Analytics Engineer Jobs

As a Data Analytics Engineer I, you'll bridge engineering and analytics, manage data pipelines, collaborate with stakeholders, and utilize modern open-source tech for data transformation and integration in structured finance.

The Senior Finance Analytics Engineer designs dbt models, collaborates on metrics with finance teams, and enhances data for AI consumption while maintaining SOX compliance.

Design and maintain scalable data models and pipelines for analytics. Collaborate with teams to ensure reliable data supporting business insights.

The RevOps Analytics Engineer is responsible for maintaining data infrastructure, building reliable data systems, and supporting revenue analytics through effective data modeling and ETL/ELT processes.

Lead analytics engineering: design scalable dimensional models, build modular tested transformations, replace brittle pipelines with reusable patterns, drive semantic layers and self-service analytics, partner on data architecture, and provide cross-functional technical leadership and governance.

Develop and improve inline metrology flows and failure-analysis methods for photonic quantum hardware. Build and analyze SPC charts, perform RCA, design experiments, coordinate with software and external partners, purchase and qualify metrology tools, and apply statistical analysis to improve yield and wafer performance.

The Analytics Engineer will design data models, maintain analytics pipelines, document data governance, and partner with stakeholders to address data needs.

The Analytics Engineer will develop and maintain analytical data models, manage ELT pipelines, document data governance, and partner with stakeholders to meet their data needs.

Build and maintain scalable Python-based data pipelines and backend services for analytics and ML workflows. Design software systems, support analytics/model training and deployment platforms, implement CI/CD and IaC, manage AWS/on-prem environments, monitor and improve pipeline reliability, and evaluate new AI technologies to increase platform efficiency.

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 Data Engineer will build and optimize ETL pipelines, manage data integration, and develop data models to enable analytics for marketing and product insights.

The AI Developer is responsible for designing and deploying AI solutions, including autonomous agents and predictive models, and integrating them into business operations.

Responsible for managing the company website and marketing technology, ensuring technical stability and analytics tracking, supporting campaign performance, and optimizing digital experiences.

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.

As a Senior Full Stack Software Engineer, you will own product features, design scalable systems, mentor teammates, and ensure coding excellence while collaborating with cross-functional teams.

Design and implement high-performance, parallel algorithms in C++ and CUDA to accelerate dataframe and database operations. Contribute to open-source projects (cuDF, Velox, Presto, Spark), profile and optimize code, and collaborate with GPU hardware and software experts to build scalable data-processing libraries.

Lead an analytics implementation for Valvoline's Global Products segment, driving metrics standardization, reporting consistency, and data accessibility. Create a scalable data framework, improve decision-making through visual analytics, and coach internal teams on analytics best practices.

The role involves leading analytics implementation for Valvoline's Global Products, focusing on standardizing metrics, enhancing reporting, and building scalable analytics infrastructures using SAP Datawarehouse Cloud.

The role involves leading the implementation of an analytics solution for Valvoline's Global Products business segment, focusing on standardization and visualization of metrics, data access, and analytics capabilities.

The role involves leading analytics solutions for Valvoline's Global Products segment, implementing a comprehensive data framework, and enabling insights through effective visualization and analytics practices.

Lead the development of analytics infrastructure for clinical AI/ML products, focusing on product performance monitoring, data management, and cross-functional collaboration.

The Senior E Commerce Developer will lead Agile teams, oversee development, mentor developers, manage technical debt, and ensure flexible and maintainable engineering solutions for eCommerce platforms.