Top Remote Data Engineer Jobs

The Sr. Healthcare Data Engineer designs and delivers analytics, collaborates across departments, and ensures data accuracy to support financial decision-making.

As a Data Engineer at Edmunds, you will architect and maintain data platforms for analytics and AI/ML, ensuring scalable, reliable data processing and supporting cross-functional collaboration.

The role involves building large, scalable analytics pipelines, defining data models, integrating data, and collaborating on data architecture and strategies.

The Data Engineer will design and build scalable data systems, contribute to the architecture of the data platform, and collaborate with AI/ML engineers to enhance automation and intelligence in Canoe's systems.

As a Data Engineer, you will transform raw healthcare data into quality intelligence products, lead product development, and mentor junior engineers while collaborating cross-functionally.

The Data Engineer will help build modern data infrastructure, designing ETL pipelines, modeling datasets, and collaborating with teams for improved data quality and accessibility.

As a Data Engineer, you'll lead data engineering projects, develop data transformations, build workflows with Apache Airflow, and ensure data quality and integrity while collaborating with stakeholders.

Lead analytics engineering initiatives, design data pipelines, develop business intelligence solutions, and ensure data governance while collaborating with stakeholders.

The Data Engineer will architect and develop robust data frameworks for data platforms, focusing on data transformations and automated workflows. Responsibilities include collaborating with stakeholders, ensuring data quality, and maintaining high engineering standards.

As a Data Engineer II at Magnite, you will build and optimize data pipelines with Apache Spark and Python, collaborate on data architecture, ensure operational performance, and work on infrastructure provisioning using Terraform and AWS.

The Data Engineer will build and maintain data pipelines, optimize workflows, manage infrastructure, and enhance pipeline observability while collaborating with teams for effective data delivery.

The Principal Data Engineer at NBCUniversal leads the development of data applications, manages data pipelines, and collaborates with teams while coaching junior engineers. Responsibilities include designing scalable data solutions and integrating AI technologies.

As a Data Engineer II, you will build, scale, and optimize data platforms, focusing on ETL/ELT pipelines, and collaborate with data scientists and AI engineers to support data-driven applications and insights.

The Principal Data Engineer will lead data engineering efforts on public cloud, design scalable solutions, build data pipelines, and drive deliverables with a high level of technical expertise in relevant technologies.

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

The Principal Data Engineer will design, implement, and lead data solutions, working closely with teams using technologies like Azure Databricks and Kafka, mentoring junior engineers, and improving CI/CD and DataOps practices.

Design and implement ETL pipelines, optimize data systems, build data warehouses, and develop AI/ML models for data solutions. Collaborate with teams to deliver data-driven products and ensure data quality and governance.

The Senior Data Engineer will design, develop, and maintain ETL workflows and pipelines, optimize performance, troubleshoot ETL processes, and ensure data quality in a healthcare setting.

We're seeking a Data Engineer with 5+ years of experience to build data processing solutions using Python, design data models, and process large data streams while ensuring high performance across various data technologies.

The Senior Data Engineer will design data models, build and manage ETL pipelines, contribute to data governance, and explore integrations with AI. Responsibilities include collaboration with teams to ensure data quality and consistency.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.

The Staff Data Engineer will lead design and implementation of analytics platforms and data products, collaborate cross-functionally, mentor engineers, and drive best practices at Upside.

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.