1,680 Data Engineering jobs available for remote work from home. Apply for positions such as Senior Data Architect, Lead Consultant Data Engineer (DHS), Senior DevOps Engineer (NOAA badge required), and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design and lead enterprise data architecture strategies, including the implementation of scalable data platforms and ETL/ELT pipelines. Collaborate with AI teams to build architectures supporting GenAI and machine learning workloads while ensuring data governance and quality.
Design and build modern data solutions, including data lakes and scalable data pipelines using batch and streaming technologies. Collaborate with cross-functional teams to ensure data availability, quality, and integration within client environments.
Lead the design and implementation of scalable, secure cloud-native solutions on AWS and Azure using infrastructure as code. Collaborate with security experts and technical teams to optimize CI/CD pipelines and automate operational workflows.
Design, develop, and optimize scalable data pipelines and analytics solutions using the Databricks platform. This includes implementing ETL/ELT processes, managing data replication via HVR, and collaborating with data scientists for ML workloads.
Architect and build the core data infrastructure and self-service frameworks to enable enterprise-scale data engineering. Define the long-term technical roadmap for the Data Lakehouse and implement global governance and AI-driven data ingestion systems.
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The role involves partnering with cross-functional teams to deliver actionable analyses and building scalable reporting dashboards. You will develop and automate data pipelines to drive business growth and operational efficiencies across the organization.
Lead the design and implementation of scalable, secure cloud-native solutions on AWS and Azure using infrastructure as code. Maintain CI/CD pipelines and develop automation scripts to streamline operational workflows and support Generative AI applications.
Design, build, and operate automated real-world data delivery pipelines using dbt, PySpark, and AWS architecture. Manage delivery operations, ensure HIPAA compliance, and serve as the primary technical contact for channel partner data inquiries.
Own the long-term architecture and evolution of the analytics engineering platform to ensure data models are scalable and AI-ready. Establish technical standards for modeling, testing, and documentation while partnering with stakeholders to improve warehouse reliability.
Lead the implementation of a scalable data quality and observability framework using GX Core to detect and prevent data issues. Establish validation standards, maintain data lineage, and integrate quality checks into CI/CD pipelines to improve business confidence.
Drive business growth by selling data, analytics, and informatics services to biotech and pharma companies in the New England area. Identify new prospects, manage the sales pipeline, and collaborate with technical teams to deliver consultative solutions.
Design and maintain data pipelines to support AI model training and evaluation workflows. Develop automation tools for data collection and labeling while collaborating with ML researchers to improve model performance.
Plan and direct the development of AI solutions to improve security detection and response, ranging from classical ML to agentic systems. Lead technical teams, manage the AI roadmap, and partner with cross-functional stakeholders to deliver scalable production-grade AI.
Design scalable and performant applications using MongoDB while guiding customers on architecture patterns and optimization strategies. Partner with sales teams to drive account success through technical discovery, demos, and pipeline generation.
Design and architect scalable systems using MongoDB to solve complex business problems for enterprise customers. Partner with sales teams to drive technical discovery, deliver demos, and ensure long-term customer success.
Lead teams focused on developer productivity and the AXIS team to improve the software development lifecycle through metrics and observability. Drive the roadmap for AI-driven development and provide technical leadership to foster a culture of innovation and efficiency.
Lead teams focused on developer productivity and the AXIS team to improve the software development lifecycle through metrics and observability. Drive the roadmap for AI-driven development tools and provide technical leadership to foster a culture of innovation and efficiency.
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Architect and lead the long-term technical roadmap for the enterprise Data Lakehouse, focusing on high-performance engines and self-service frameworks. Build internal SDKs and orchestration tools to abstract cloud complexity and implement global data governance and AI ingestion pipelines.
Design, develop, and deploy scalable data infrastructure and pipelines using the Databricks platform and Medallion Architecture. Lead data engineering initiatives, including API integrations and automated CI/CD deployments via Azure DevOps.
Develop and manage scalable data pipelines and architectures using Snowflake and cloud-native platforms. Collaborate with client stakeholders to deliver high-quality data ingestion, transformation, and governance solutions.
Lead the strategy, design, and execution of technical training programs to scale engineering talent development. Optimize training operations and establish measurement frameworks to ensure high-quality technical output and ROI.
The role involves bridging the gap between unstructured real-world clinical data and AI models by designing data dictionaries and harmonizing data pipelines. You will act as the technical interface with global partners to ensure data integrity and automate cleaning tasks using Python.
The role involves bridging the gap between unstructured real-world clinical data and AI models by designing data dictionaries and harmonizing data pipelines. You will act as the technical interface with global partners to ensure data quality and reproducibility using Python.
Design and implement production-grade machine learning systems to enhance threat detection and automate security analysis for ICS and xOT cybersecurity. Collaborate with data engineers and OT experts to build scalable ML workflows and optimize model performance in cloud and on-premises environments.
Design and implement production-grade machine learning systems to enhance threat detection and automate security analysis for ICS and xOT cybersecurity. Collaborate with data engineers and OT experts to build scalable ML workflows and optimize model performance in production.
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Lead the re-architecture and modernization of core data systems to enable scalable and secure pipelines for cloud and on-prem environments. Collaborate cross-functionally to create analytics for discovering IOCs on xOT assets and align team efforts with the company's data strategy.
Design and implement sustainable data contracts and transformation layers to support performant analytics. Collaborate with product engineering teams to deliver data solutions and establish shared tooling for observability and lineage tracking.
Lead the design and implementation of enterprise-scale Data and AI platforms, focusing on scalable architectures and governance. Drive the adoption of Generative AI and Agentic AI solutions to modernize business capabilities.
Implement and operate the enterprise data governance program to strengthen data quality, stewardship, and regulatory compliance. Lead the strategic transition of the organization from a Data Processor to a Data Controller while partnering with cross-functional teams.
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