2,404 Data Engineer jobs available for remote work from home. Apply for positions such as Data Engineer, Data Engineer, DATA ENGINEER and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Build and maintain end-to-end data pipelines in the Azure stack, moving data from source systems into Data Lakes and SQL databases. Develop data warehouse layers using T-SQL and deliver insights through Power BI semantic models and reports.
Design and manage advanced data systems and pipelines on GCP to convert raw player data into actionable insights. Develop APIs, CI/CD pipelines, and maintain data governance standards including GDPR/CCPA compliance.
Build and maintain scalable data pipelines, platforms, and models to create tangible business value for customers. Translate business requirements into actionable technical tasks within modern cloud ecosystems.
The role involves playing a crucial part in building, managing, and maintaining large-scale data infrastructures. The engineer will focus on integrating data solutions using Databricks and other cloud technologies.
The role involves designing and operating end-to-end data solutions using Microsoft Fabric, Azure, and the Power Platform to digitize business processes. The candidate will own data architecture, BI dashboard development, and the migration of legacy on-premise systems to the cloud.
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Own the data plane by building ingestion pipelines and transformation layers to turn messy insurance data into clean datasets. Model and tune data across Postgres and ClickHouse to power analytics and AI products.
Design, build, and support end-to-end data pipelines, APIs, and migrations on Azure to power web and mobile applications. Ensure data accuracy and integrity through mapping, transformation, and validation across multiple systems.
Design and build scalable data pipelines and models to create a digital twin of Nscale's operational signals. Develop trusted datasets and metrics to enable self-serve analytics for capacity planning, cost optimization, and customer reporting.
Design, build, and optimize scalable data processing systems and ETL/ELT pipelines in cloud and on-prem environments. Support the migration of legacy DWH systems and implement monitoring and alerting for data processes within an Agile framework.
Responsible for managing and extending BigQuery data pipelines to extract meaningful signals from large, inconsistent geospatial and device datasets. The role involves owning pipelines end-to-end and creating web-based dashboards for data visibility.
The role involves working as a Data Engineer within a dynamic team of analytics experts. Responsibilities include data integration, ETL processing, and managing big data environments.
Responsible for extracting, transforming, and analyzing data using SQL and Python to design and maintain ETL processes. The role involves developing dashboards and collaborating with stakeholders to translate business needs into analytical solutions.
Design, develop, and maintain squad-specific data architectures and pipelines following ETL and data lake principles. Develop data products for analytics and ML engineers while mentoring other professionals on data standards.
Design and maintain squad-specific data architectures and pipelines following ETL and data lake principles. Develop data products for analytics and ML engineers while mentoring other data professionals on best practices.
Design, develop, and maintain squad-specific data architectures and pipelines following ETL and data lake principles. Develop data products for analytics and ML engineers while mentoring other data professionals on standards and best practices.
Design, build, and operate batch and real-time data pipelines using Azure, Databricks, and Python. The role involves developing data solutions for either the Data Science team for ML forecasting or the Data Streaming Platform team for real-time data scaling.
Build and scale high-performance ETL/ELT pipelines and data services to convert raw connectivity data into actionable intelligence. Develop APIs using FastAPI and manage data transformations with DBT to optimize warehouse performance.
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Design, develop, and maintain scalable data pipelines to integrate data from various source systems like ERP and MES. Collaborate with architects and scientists to transform raw data into high-quality data products for business decision-making.
Build and maintain data ingestion pipelines and dbt models within a Snowflake warehouse on AWS. Collaborate with BI teams to translate needs into reliable data engineering work and manage operational on-call responsibilities.
Maintain, troubleshoot, and optimize a data ingestion pipeline using Java and Python. Collaborate with data scientists and engineers to improve observability and ensure high-quality data flow.
Design and implement scalable data workflows, pipelines, and streaming technologies on Kubernetes and AWS. Ensure the reliability, security, and compliance of the data layer in accordance with DoD regulations.
Architect and maintain scalable ELT pipelines using Snowflake and dbt to provide clean data for analysts and scientists. Act as a technical lead by defining best practices, conducting code reviews, and mentoring junior engineers.
Design and implement scalable, domain-oriented data pipelines on AWS to support analytics and business-critical workflows. Collaborate with cross-functional teams to ensure data quality, reliability, and performance across various data domains.
Build and maintain scalable, reliable data pipelines and govern performant cloud-deployed relational and non-relational databases. Collaborate on secure architecture definitions to drive data systems toward near real-time performance.
Design, develop, and maintain ELT pipelines and data models to ensure data integrity within the warehouse. Collaborate with cross-functional teams to translate business requirements into scalable analytical solutions and actionable insights.
Build and scale reliable data pipelines from ingestion to delivery while establishing dbt best practices and data standards. Create self-service tooling and AI agents to empower cross-functional teams to independently access and analyze data.
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Design and implement scalable data architecture and ETL solutions to integrate data from various sources into on-prem and cloud platforms. Provide technical leadership and support for analytics systems while collaborating with stakeholders to define business requirements.
Architect and optimize daily ingestion pipelines for over 14 million listings while scaling AWS RDS PostgreSQL and Aurora databases. You will design robust ETL processes and build monitoring tools to ensure the reliability and speed of the data infrastructure.
The Data Engineer will support the scaling of Stord's commerce-enablement technology and fulfillment services. They will help manage data across OMS, Pre- and Post-Purchase, and WMS platforms to improve consumer experiences.
Design and maintain scalable AWS data platforms and pipelines for batch and streaming workloads. Implement data governance, normalization workflows, and knowledge graphs to support analytics and AI/ML use cases.
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