1,204 Data Engineer jobs in United States available for remote work from home. Apply for positions such as Senior Data Engineer, Data Management & BI, Managing Engineer, Data Engineering, Data Engineer / Platform Administrator (Azure Databricks) and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design, build, and maintain scalable data pipelines to support analytics, operational reporting, and data-driven decision-making. Collaborate with cross-functional teams to translate business requirements into reliable technical solutions and establish engineering standards.
Lead the design, development, and delivery of scalable data solutions while mentoring and coaching a team of data engineers. Partner with cross-functional stakeholders to translate business needs into technical roadmaps and ensure high-performing, secure data products.
The role involves administering an Azure Databricks environment by managing workspaces, automation, and performance monitoring. Additionally, the engineer will design and optimize data pipelines to support various source systems and internal stakeholders.
Serve as a subject matter expert for advanced data center thermal management and liquid cooling systems. Develop integrated cooling concepts and support system validation through digital analysis, laboratory testing, and field evaluation.
Data engineers at Netflix build and maintain efficient systems to process and model data across various business domains. They collaborate with cross-functional teams to power analytics, product features, and machine-learning models.
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The Data Engineer II is responsible for managing and improving streaming, batching, and event-based data pipeline solutions. They will collaborate with business users to integrate data from multiple sources and ensure its availability for reporting and system integration.
The Data Engineer will design, implement, and optimize data systems and pipelines to support AI/ML applications for a Navy IT command. Responsibilities include defining data requirements, establishing data architectures, and automating software-intensive solutions.
The Senior Data Engineer II will own and evolve the end-to-end data pipeline architecture, making critical decisions regarding scalability, cost, and reliability. They will lead technical initiatives, mentor team members, and partner with cross-functional stakeholders to improve platform health and developer experience.
You will lead the design and architecture of complex backend systems within the Datastore, including data models, event pipelines, and GraphQL APIs. You will collaborate with cross-functional teams to translate requirements into scalable data infrastructure solutions while mentoring other engineers.
Design, build, and maintain scalable data pipelines and analytics-ready data products using cloud-native technologies. Collaborate with cross-functional teams to integrate data from various sources while ensuring data quality, lineage, and reliability.
Design, build, and operate large-scale data processing pipelines and analytics platforms using the Hadoop ecosystem. Ingest, transform, and analyze massive volumes of structured and unstructured data to support enterprise analytics and machine learning workloads.
The Cloud Pipeline Data Engineer will automate data ingestion and transformation processes for a government financial reporting system using AWS services. Responsibilities include maintaining ETL pipelines, performing database tuning, and contributing to infrastructure-as-code development.
Design and maintain semantic data models, metrics layers, and dashboards to provide a consistent source of truth for business analytics. Collaborate with stakeholders to build secure data pipelines and enable self-service analytics while ensuring data quality and governance.
The role involves testing and troubleshooting core EDI transactions to ensure accurate data flow between healthcare systems and trading partners. You will diagnose transaction-level errors, lead testing cycles, and act as a liaison between technical and non-technical teams to resolve production issues.
You will design and deliver backend systems and user interfaces while optimizing data operations for performance and scalability. Additionally, you will contribute to data modeling, API development, and the maintenance of automated testing suites.
The Lead Data Engineer will own the end-to-end data platform, including the Snowflake data warehouse, semantic layer, and identity resolution. They are responsible for setting company-wide data standards, enabling AI agents as data consumers, and ensuring high-quality documentation.
You will develop and deploy data pipelines and platforms to organize disparate data from sources like IoT and EHR systems. You will work in a multi-disciplinary team to support the design, maintenance, and scaling of data platforms for mission-driven projects.
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You will design, build, and maintain scalable data platforms while developing pipelines to organize disparate structured and unstructured data. You will also lead cross-functional teams to deliver advanced technology solutions for mission-driven projects.
The Lead Data Engineer will own domains of the data platform, setting technical direction and managing a team of senior and mid-level engineers. They are responsible for developing roadmaps, establishing engineering standards, and ensuring the accuracy and timeliness of client data feeds.
You will serve as the primary architect for the enterprise data infrastructure, building self-service frameworks and high-performance engines. Additionally, you will lead cross-functional architecture reviews and define the long-term technical roadmap for the company's data lakehouse.
Design, build, and evolve knowledge graphs in Stardog while integrating heterogeneous data sources into a unified semantic layer. Collaborate with cross-functional teams to align models with life science standards and automate graph lifecycles through CI/CD pipelines.
Design, implement, and deploy end-to-end data and AI/ML systems on AWS while maintaining production platforms for reliability and scalability. Collaborate with cross-functional teams and AWS Professional Services to integrate agentic AI into enterprise operations.
Design and operate real-time and analytical data pipelines using Azure Data Explorer to support enterprise reporting and decision-making. Collaborate with cross-functional teams to develop data models, ensure data quality, and create business-ready visualizations.
The Analytics Data Engineer will design, develop, and maintain scalable data pipelines and systems using Databricks and cloud tooling to support data-driven decision-making. They will also leverage advanced analytics and AI to analyze program data, identify automation opportunities, and ensure data quality through robust lifecycle processes.
You will design and scale automated data engineering systems, including agentic pipelines and ML infrastructure, to support a high-growth e-commerce business. You will also collaborate cross-functionally with data scientists and analysts to ensure the reliability and performance of shared data assets.
Design, build, and maintain scalable data solutions while providing technical guidance for complex data architecture. Collaborate with stakeholders to optimize data warehouse requirements and drive continuous improvement in data quality and automation.
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You will build production software and data systems beyond traditional ETL pipelines for a premier banking client. The role involves architecting real-time, event-driven data streams and working hands-on with cloud-native technologies.
Develop and design heat rejection and HVAC systems for data centers, ensuring optimal performance, redundancy, and energy efficiency. Conduct CFD simulations to optimize airflow and coordinate mechanical infrastructure with electrical and other critical systems.
The Senior Mechanical Engineer will design and optimize HVAC and heat rejection systems for data centers, ensuring redundancy, energy efficiency, and compliance with industry standards. The role involves conducting CFD simulations, performing heat load calculations, and coordinating with cross-functional teams to support mission-critical infrastructure projects.
You will architect and lead the development of data ingestion, modeling, and synchronization systems to create a near-real-time knowledge graph of the developer ecosystem. Additionally, you will define operational readiness and mentor senior and intermediate engineers to ensure high-velocity delivery of data products.
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