Remote Data Jobs · US

Seeking a Data Architect / Principal Data Engineer to join our development center, working with a major US client in a fast-paced, high-impact environment. In this role, you will define, architect, and implement scalable data platforms and end-to-end ELT pipelines aligned with modern Lakehouse principles. You will work closely with cross-functional teams across the US, Colombia, and Brazil to ensure that our data ecosystem is reliable, future-proof, and aligned with enterprise architecture standards.

In this role, you will define, architect, and implement scalable data platforms and end-to-end ELT pipelines aligned with modern Lakehouse principles, collaborating with cross-functional teams across the US, Colombia, and Brazil. This position requires deep technical expertise, strong architectural thinking, and the ability to influence and mentor engineering teams. Fluent English communication is essential for collaborating with global stakeholders, presenting architectural recommendations, and ensuring alignment across distributed teams.

Maven Clinic is looking for a Strategic and customer-focused Senior Data Analyst specializing in Customer Analytics, who will help Maven Clinic’s customers understand, measure, and amplify clinical and business value through data with experience in developing scalable analytics solutions and align cross-functional stakeholders, turning data into actionable insights that drive client outcomes and strengthen long-term partnerships.

In this role, you will support two large engineering organizations by managing end-to-end headcount processes, driving data accuracy, and delivering insights that inform workforce planning and operational decisions. You will work closely with senior leaders to maintain clean organizational structures, partner on hiring-related initiatives, and build/maintain reporting dashboards that support business operations at scale.

Architect, build, and operate real-time/batch ETL pipelines, agentic orchestration flows, and AI/ML endpoints for autonomous, multi-agent production systems. Contribute actively to team processes, documentation, and operational quality. Build event-driven data workflows, integrate with various connectors, and expose agentic features.

The Senior Software Engineer - Data will architect, implement, and optimize data models, pipelines, and storage solutions across Acquisition.com’s data ecosystem, ensuring reliability, performance, and accessibility of data. This individual will serve as a bridge between raw information and actionable business intelligence, taking complex data initiatives from concept to delivery.

As a Data Scientist on Plaid’s Fraud Data team, you will analyze customer and network traffic to understand how Protect performs across different segments and use cases. You’ll build dashboards and performance metrics that create a clear, shared view of product health for both the team and our go-to-market partners.

As a Data Engineer on the Growth org, you will collaborate with our cross-functional partners in Data Science, Product, and Finance to build and maintain high quality data sources and build software that maximizes the value and efficacy of that data. The team operates independent of skill set, so your peers with software engineering backgrounds will execute on data engineering work, and you will make contributions on software systems that don’t directly work with our data systems.

This role centers on analyzing large-scale research and clinical datasets, developing and validating deep learning models for wearable sensor data, and collaborating with cross-functional teams to translate findings into production features and scientific publications. Your work will directly contribute to improving health outcomes for Oura members.

As a Data Integration Engineer III, you will be an integral member of an Agile sprint team. You'll partner closely with Business Systems Analysts, Data Engineers, and cross-functional stakeholders to deliver scalable, high-quality data integration solutions, build and maintain data pipelines, and resolve data issues to improve data health.