2,107 Data Engineering jobs available for remote work from home. Apply for positions such as Senior Software Engineer, Senior Analytics Engineer, Senior Data Scientist , and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The Senior Software Engineer will perform innovative software development, data engineering, and product support within an Agile Scrum team. They are responsible for designing, testing, and debugging software solutions while collaborating with stakeholders to deliver high-quality, scalable technology.
You will architect and implement reusable analytical data products and semantic layers to power decision-making across the organization. This involves collaborating with cross-functional teams to define canonical entities, ensure data quality, and establish technical governance.
The Senior Data Scientist will partner with Product and Engineering teams to drive product-led growth through rigorous experimentation and behavioral analysis. They will build analytical frameworks, identify friction points in the user journey, and translate data insights into actionable product strategies.
You will build and maintain AI-ready data pipelines, semantic views, and governed metrics on Snowflake to support AI assistants and agents. Additionally, you will collaborate with cross-functional teams to ensure data quality, traceability, and reliability across automotive industry data products.
You will own and drive the development of Minerva, Airbnb's semantic layer and metrics platform, to ensure reliable data insights across the company. This involves scoping ambiguous problems, building core services, and partnering with cross-functional teams to improve data queryability and reliability.
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The Senior Manager of Marketing Analytics will own the end-to-end measurement of marketing performance, including attribution, funnel health, and pipeline forecasting. They will also integrate AI-driven insights into the marketing stack to optimize budget allocation and provide actionable data to leadership.
Develop and maintain predictive models for credit risk, including probability of default and loss given default. Collaborate with cross-functional teams to integrate model outputs into underwriting, fraud detection, and collections strategies.
The manager will oversee client reporting, compliance reporting, and performance analytics while leading a team of analysts. They are responsible for maintaining data quality, building dashboards, and optimizing SQL queries against large-scale healthcare claims datasets.
The ETL Developer designs, architects, and implements complex data solutions using Azure and Microsoft Fabric to support rural health transformation initiatives. They are responsible for monitoring data quality, managing pipeline performance, and collaborating with functional teams to meet business requirements.
The Senior Data Engineer will design, build, and maintain scalable data infrastructure and ingestion frameworks to support data-driven reporting. This role involves collaborating with cross-functional teams to implement data governance, optimize performance, and mentor junior engineers.
The Senior Data Engineer will design, develop, and maintain reliable ETL/ELT pipelines while ensuring data quality through cleansing, matching, and reconciliation. They will also build standardized data models and collaborate with stakeholders to support reporting and application requirements.
Build and maintain dbt models on Snowflake to transform sales, subscription, and hierarchy data into clean, documented datasets. Collaborate with sales and finance partners to ensure data accuracy, reconcile discrepancies, and support leadership dashboards.
Design, develop, and deploy AI-powered solutions and automations to optimize DevOps workflows and infrastructure. Manage and monitor Azure resources, Databricks workspaces, and CI/CD pipelines while ensuring secure and efficient operations.
The Senior MLOps Engineer will lead the design and evolution of platforms and workflows to enable machine learning teams to develop, train, and deploy systems at scale. They will collaborate across data science and engineering teams to drive model lifecycle improvements, governance practices, and infrastructure automation.
You will build and maintain reliable data pipelines, semantic models, and governance frameworks to support decision-making across the business. Additionally, you will design systems to integrate AI-assisted analytics and ensure high-quality data availability for both human analysts and AI agents.
You will design and implement scalable data infrastructure, pipelines, and models while driving code quality and engineering best practices. Additionally, you will partner with the Risk team to build automated reporting pipelines and consolidate siloed datasets into unified models.
You will design and implement a scalable claims data model and architecture while collaborating with AI teams to build end-to-end solutions. Additionally, you will be responsible for extracting, cleansing, and modeling claims data to ensure high accuracy and quality for downstream operations.
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You will build and operate a hybrid Kubernetes platform while managing infrastructure across a multi-account AWS environment. You will also partner with internal teams to deliver environments, maintain CI/CD pipelines, and participate in an on-call rotation to ensure system reliability.
Build and maintain dbt models on Snowflake to transform sales, subscription, and hierarchy data into clean, documented datasets. Collaborate with sales and finance partners to ensure data accuracy, monitor model performance, and support leadership dashboards.
The AI Data Analyst will design, develop, and maintain data pipelines and architectures to support artificial intelligence and machine learning solutions. They will collaborate with cross-functional teams to clean datasets, manage data flows in Google Cloud, and provide technical support for AI systems.
The Incident Management Coordinator operates the Central Incident Board by receiving, classifying, and routing incidents to the appropriate technical teams. They are responsible for driving major incidents, managing stakeholder communication, and ensuring the quality of operational data through accurate ticket lifecycle management.
The Incident Management Coordinator operates the Central Incident Board by receiving, classifying, and routing IT incidents to the appropriate engineering teams. They are responsible for managing the ticket lifecycle, driving major incident resolution, and ensuring accurate service reporting and SLA compliance.
The Senior Project Manager will lead and motivate teams using waterfall, agile, and hybrid methodologies to deliver high-visibility information security and IT projects. They are responsible for managing project scope, schedules, risks, and cross-functional collaboration to ensure business value is achieved.
You will design, build, and maintain analytical data models and transformation layers to turn high-volume building telemetry into trusted datasets. Additionally, you will define core business metrics and partner with cross-functional teams to support customer-facing reporting and internal decision-making.
The Lead Data Analyst translates business needs into actionable data requirements and integrated solutions while partnering with cross-functional teams. They are responsible for data profiling, solution validation, and identifying opportunities for business process automation to drive measurable outcomes.
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The Senior Data Engineer will industrialize and optimize dbt pipelines while migrating workflows from DuckDB to PostgreSQL. They will also define data contracts and build scalable onboarding processes to support business expansion.
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You will industrialize and optimize dbt pipelines while migrating workflows from DuckDB to PostgreSQL. Additionally, you will define data contracts and build scalable onboarding processes to support expansion into new markets.
The Data Engineering Specialist will build and operate large-scale data systems to support AI training and evaluation pipelines. Responsibilities include managing data ingestion, transformation, quality assurance, and high-throughput delivery for diverse AI model training tasks.
Design, develop, and maintain enterprise Java applications to modernize eligibility and enrollment systems for the Department of Veterans Affairs. Collaborate with architects to optimize database integrations and participate in CI/CD processes and code reviews.
The Senior Marketing Analyst will own the measurement and performance improvement of B2B pipeline and B2C growth marketing strategies. This role involves building analytical foundations, managing attribution models, and providing actionable insights to leadership to drive marketing efficiency.
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