2,411 Data Engineer jobs available for remote work from home. Apply for positions such as AI Engineer - Automation & Data Integration, Data Warehouse Test Engineer, Data Warehouse Integration Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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You will design and implement integration and automation systems that orchestrate connectors and manage data streams. Additionally, you will be responsible for developing backend solutions and integrating LLM-driven processes into productive workflows.
The Data Warehouse Test Engineer will perform functional, regression, and integration testing on complex data systems. They are responsible for data reconciliation, validation, and writing detailed defect reports to ensure high data quality.
The engineer will support the development, maintenance, and enhancement of enterprise data warehouse integrations and related system interfaces. Responsibilities include managing Informatica PowerCenter workflows, performing system tuning, and maintaining comprehensive data mapping documentation.
Lead the design and implementation of scalable data pipeline architectures while defining engineering standards and platform best practices. Act as the primary technical reference for client stakeholders and mentor team members to ensure high-quality delivery of data engineering programs.
The AI Engineer will design, develop, and deploy advanced AI solutions, including Generative AI, across healthcare technology platforms. This role involves building machine learning models, integrating them into existing systems, and ensuring compliance with healthcare regulatory standards.
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Manage hyperscale data center construction projects from initiation through completion, including planning, design, and construction oversight. Review mechanical system designs, provide technical direction to consultants, and resolve construction-related engineering issues.
You will manage and operate the Apache Kafka backbone, Debezium data pipelines, and Kubernetes-based workloads. Additionally, you will act as a senior technical partner to drive design reviews and automate infrastructure management.
The Data Center Constructability Engineer will own the constructability process from site due diligence through design review and pre-construction planning to ensure modular data center designs are buildable. They will develop standardized construction playbooks and act as the primary technical liaison between product engineering, fabricators, and general contractors.
Design and implement modern lakehouse architectures using Microsoft Fabric and Databricks while building performant ELT/ETL pipelines. Deliver complex Power BI reports and semantic models while acting as a trusted technical advisor to enterprise clients.
The Lead NOC Engineer will provide technical leadership for incident response and operational ownership of modular, edge, and distributed data center environments. They are responsible for mentoring junior staff, ensuring infrastructure uptime, and driving continuous improvement in reliability and MTTR.
The Technical Solutions Architect will serve as a technical leader and trusted advisor, providing deep expertise in WAN routing, data center connectivity, and network infrastructure. They will collaborate with sales and engineering teams to design scalable architectures, conduct proof-of-concepts, and drive customer success through technical enablement.
The role involves designing and developing enterprise-scale BI solutions using Power BI and modern data architecture paradigms like Data Fabric. You will also be responsible for defining data products, managing data governance, and collaborating with stakeholders to enable self-service analytics.
The role involves designing and maintaining common data models for Zero Trust maturity, implementation evidence, and outcome measures. You will also develop analytics to measure capability maturity and partner with specialists to streamline data refresh and visualization workflows.
The engineer will design and deploy data center infrastructure, including power, cooling, and network hardware across various POP sites. They are responsible for creating technical documentation, managing vendor projects, and providing support to network engineering teams.
The HPC Engineer will solve complex AI problems for customers and integrate cutting-edge AI technologies into CAE workflows. They will also collaborate with the development team to enhance AI software products and provide tailored solutions to customer needs.
Design, deploy, and operate VMware-based virtualization, software-defined networking, and software-defined storage platforms. Manage capacity and automation across on-premises and hybrid cloud environments.
You will own the data layer and design the analytics architecture, including a tiered platform for system of record, low-latency serving, and batch/ML processing. You will also be responsible for database performance, schema modeling, and implementing observability to ensure system reliability.
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You will design and implement scalable AWS architectures for data platforms, ML workloads, and generative AI solutions. Additionally, you will act as a trusted technical advisor to clients, supporting pre-sales activities and mentoring junior team members.
The Principal Data Center MEP Engineer will lead engineering design and analysis projects for mission-critical data center systems. This role involves developing detailed documentation, conducting site inspections, and providing strategic leadership to ensure project success and collaborative innovation.
The Senior Data & Analytics Engineer will build and maintain governed data models and semantic assets to enable domain self-service on the Databricks platform. This role involves partnering with business stakeholders to translate requirements into testable transformation logic while ensuring enterprise consistency.
Participants will export historical financial data from various personal apps and services while ensuring all personally identifiable information is redacted using a provided tool. They must submit these redacted files along with self-created financial artifacts for quality review and potential rework.
You will lead the design, architecture, and implementation of high-performance data center network solutions for AI and enterprise environments. Additionally, you will collaborate with cross-functional teams to automate network operations and provide expert guidance throughout the customer engagement lifecycle.
Lead the design, technical validation, and optimization of advanced thermal management systems for hyperscale data centers. Design cooling infrastructure and perform CFD modeling to ensure efficient thermal containment for AI compute hardware.
You will design, build, and maintain scalable data infrastructure and pipelines to process high-bandwidth sensor logs from autonomous vehicles. Additionally, you will develop tools for dataset curation, labeling, and visualization to support perception, planning, and simulation engineering teams.
The Data Warehouse Test Engineer will design and execute complex functional, regression, and integration test suites for AI/ML and data systems. They are responsible for validating AI-generated SQL queries against multi-table star schemas and documenting precise defect reports.
The role involves owning and optimizing the data pipeline and API infrastructure to ensure high performance, reliability, and scalability as the device fleet grows. You will collaborate across teams to turn raw telemetry into actionable tooling while maintaining production health and reducing technical debt.
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You will design and maintain high-performance backend microservices and automation workflows to modernize enterprise sales processes. Additionally, you will integrate custom backend solutions with Salesforce and build systems to support AI-driven sales development tools.
You will design and build the data foundation and LLM-powered intelligence layer to transform creative strategy into a data-driven process. This includes managing end-to-end features, from data pipelines and search layers to the web-based dashboards and interfaces.
You will build and ship full-stack features for infrastructure cost and usage tooling, including interactive web applications and backend services. You will also partner with data and analytics engineers to design data models and launch products for analyzing AI productivity and cloud efficiency.
The Data/Context Engineer will architect and scale a multi-regional knowledge base system to support decision-making across 12 regions. Responsibilities include building ingestion pipelines, managing retrieval evaluation, and ensuring data integrity through health reporting.
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