1,201 Data Engineer jobs in United States available for remote work from home. Apply for positions such as Senior Data Engineer, Lead Data Engineer, Senior Data Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The Senior Data Engineer will build and maintain tested dbt models to support financial reconciliation and consistent metric definitions across the platform. They will also design scalable data ingestion pipelines and implement controls to ensure data quality and reliability.
You will design, maintain, and improve data pipelines and infrastructure across the full data lifecycle. Additionally, you will collaborate with stakeholders to define data flows, create data contracts, and provide technical guidance to the team.
Architect, design, develop, and maintain enterprise-grade data platforms and scalable data pipelines. Collaborate with cross-functional teams to deliver high-quality, governed data solutions that support analytics and machine learning initiatives.
The Senior Data Engineer will design, integrate, and implement modern data solutions while collaborating with cross-functional teams in an agile environment. They are responsible for processing payer files into the data warehouse and supporting the migration of workloads to the cloud.
Design, develop, and maintain scalable data pipelines to support the ingestion and transformation of high-volume healthcare data. Collaborate with cross-functional teams to operationalize data-driven insights and ensure the reliability and performance of the data platform.
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The Staff Data Engineer will lead data platform strategy and own the end-to-end Snowflake data lake architecture. They will collaborate with cross-functional teams to build robust data governance and scalable pipelines that support AI-driven underwriting decisions.
Design and architect scalable data systems while developing production-grade pipelines to ingest and normalize complex healthcare data. Ensure data quality, security compliance, and performance optimization while building bi-directional EMR integrations.
The Data Engineer will manage data implementations, production, quality, and security while executing SQL scripts for data validation. They will also collaborate with engineering teams to troubleshoot environmental issues and maintain operational dashboards.
You will strengthen data engineering and analytics services to ensure the business has access to high-quality, accurate data. This involves working closely with the engineering team to build ETL solutions, data warehouses, and analytical reporting tools.
The engineer will develop and maintain enterprise data pipelines and financial data models within the GCP environment. Responsibilities include integrating financial data from SAP into BigQuery and ensuring the reliability of daily financial reporting assets.
You will design, build, and operate the distributed services and compute infrastructure that power the company's data platform. Additionally, you will lead the technical evolution of the platform toward an AI-first architecture while mentoring team members and ensuring operational excellence.
Design, develop, and maintain scalable data pipelines and ETL/ELT processes across AWS platforms. Collaborate with business and technical teams to ensure data quality, governance, and compliance with privacy regulations.
The Principal Forward Deployed Engineer will serve as a primary technical leader for strategic accounts, driving business outcomes through hands-on execution. They will build and ship production-grade solutions while collaborating directly with customers to translate business needs into technical approaches.
Design, develop, and maintain scalable pipelines to ingest security telemetry into SIEM and cloud analytics platforms. Collaborate with cross-functional teams to ensure data quality, improve monitoring coverage, and support threat detection use cases.
The Senior Data Engineer will design, build, and maintain scalable data infrastructure, including pipelines and ETL/ELT processes, to support analytics and AI applications. They will also manage data storage patterns, ensure data quality, and collaborate with cross-functional teams to provide trusted reporting and machine learning datasets.
You will architect and build foundational data pipeline infrastructure to support a decentralized Data Mesh strategy and AI-ready semantic layers. Additionally, you will lead a small data engineering team and mentor analysts to enable self-service data product development.
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The Big Data Engineer will design, build, and operate large-scale data processing pipelines and analytics platforms using the Hadoop ecosystem. They are responsible for ingesting, transforming, and analyzing massive volumes of structured and unstructured data to support enterprise analytics and machine learning workloads.
The Lead Data Engineer will lead the development and operationalization of data pipelines, including ingestion, transformation, and quality validation. They will also guide the team in designing high-performance data structures and real-time processing applications to support business intelligence analytics.
The Lead Data Engineer will design, build, and maintain reliable data pipelines and infrastructure to support SaaS analytics. They will also supervise a Data Engineer and ensure the quality, security, and performance of data flows from various sources.
The role involves designing and maintaining scalable data pipelines in Snowflake to process complex clinical and claims data for HEDIS reporting. You will also integrate AI/ML models into workflows to automate clinical data extraction and care gap identification.
Lead and perform structural design and analysis for hyperscale and colocation data center facilities. Coordinate design deliverables with multidisciplinary teams and provide technical guidance to junior staff.
The Lead AI Engineer will design, build, and deploy production-grade AI and machine learning algorithms to support enterprise and government programs. This role involves mentoring staff, translating complex technical requirements into actionable solutions, and maintaining high-quality software standards.
The Data Engineer designs, builds, and maintains scalable data pipelines and architectures to convert structured and unstructured data into enterprise insights. They collaborate with cross-functional teams to deliver data products while ensuring high engineering standards and utilizing modern cloud-native technologies.
The Associate Data Engineer will design, build, and maintain scalable data pipelines and storage solutions for the Enterprise Individual Mastering Platform. They will collaborate with cross-functional teams to support data analytics and utilize AI tools to streamline workflows and automate tasks.
The AI Data Engineer will build and improve UI components for internal annotation tools and design efficient production workflows. They will also develop analytical dashboards and manage deployment pipelines using Azure cloud infrastructure.
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The Lead Platform Engineer is responsible for the architecture, deployment, and operationalization of AI, Microsoft Fabric, and workflow platforms across client engagements. This role involves leading internal tooling ecosystems, coordinating with development teams, and providing technical leadership for AI-powered solutions.
The Sr. Data Engineer will design and implement scalable data processes to enhance the business intelligence platform while collaborating with cross-functional teams. They are responsible for building robust data pipelines, mentoring team members, and ensuring the stability and performance of cloud-based data solutions.
The role focuses on building and maintaining robust data pipelines to ensure the reliability, accuracy, and observability of Chainlink's data systems. It involves creating scalable data models that support benchmarking, monitoring, and downstream data access for product development.
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.
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