Design, build, and launch scalable data pipelines to integrate customer datasets and financial data. Monitor pipeline reliability and translate business requirements into analytical insights to create business value.
Remote Data Engineer Jobs (2,742)
Search = Data Engineer
Design and deploy intelligent forecasting models and quotation automation agents using GCP-native services. Develop production ML pipelines and integrate model outputs into agentic workflows to drive operational efficiency.
Lead the development of critical data platform systems, focusing on scalable orchestration and streaming infrastructure. You will design multi-tenant data systems and collaborate cross-functionally to ensure operational excellence and reliability.
Intermediate Data Engineer
Berkeley Payment Solutions Inc.
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Full Time
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2 Weeks Ago
Berkeley Payment Solutions Inc.
Design, build, and maintain scalable data pipelines and infrastructure using AWS and Terraform. Partner with cross-functional teams to develop data models and ETL processes that support financial reporting and analytics.
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Design, develop, and optimize data solutions on the ADABAS platform to support enterprise data management and modernization. This includes managing database structures, performing data migrations, and ensuring system performance and security.
Solutions Engineer, Data Management
Redpoint Global Inc.
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Full Time
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2 Weeks Ago
Redpoint Global Inc.
Data Engineer (On-Site) | Engenheiro de Dados (Remoto)
Dadosfera
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Full Time
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2 Weeks Ago
Dadosfera
Design and maintain scalable ETL/ELT pipelines and layered Data Lake architectures on AWS. Implement AI and ML solutions for data quality, entity resolution, and automated attribute extraction.
Build and orchestrate data pipelines for vehicle and internal system data while maintaining an enterprise data warehouse on Snowflake. Establish data modeling standards, governance frameworks, and implement data quality monitoring and alerting.
Provide architectural oversight for the company's data platform, focusing on the design and implementation of high-quality data solutions within Palantir Foundry. Lead design reviews for data pipelines and ontology resources to ensure scalability, integrity, and alignment with enterprise standards.
The Lead Data Engineer will oversee data ETL/ELT pipelines and ensure adherence to data standards while maintaining data frameworks. This role includes collaborating with cross-functional teams to define data governance and ensuring seamless access to data for decision-makers.
Design, build, and maintain scalable ETL/ELT data pipelines and data models to support analytics and machine learning at petabyte scale. Develop production-quality Java and Python code for streaming and batch processing systems within a cloud infrastructure.
Design and build a greenfield data platform and ingestion pipelines for payment, marketing, and operational data. Implement medallion-layer transformation models and manage end-to-end orchestration using Airflow.
Design, develop, and maintain databases and ETL systems to support business intelligence and enterprise applications. Lead the creation of technical designs, automated solutions, and scalable reporting dashboards while managing production troubleshooting.
Design and scale data infrastructure and pipelines to process massive volumes of ad-tech and CRM data for real-time analytics. Develop ETL/ELT workflows and data models to optimize campaign performance and supply analysis.
Build and own an internal Data Migration Platform to extract, validate, and import data from legacy CRM systems into the core platform. Design automated workflows for data cleaning, mapping, and normalization to reduce manual migration effort.
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Build and grow the company's Data Warehouse by developing ETL/ELT pipelines and modeling payment and product data. Create clear dashboards for business teams and implement data validation tests to ensure reliable reporting.
Design, build, and maintain scalable cloud-based data pipelines and ETL/ELT processes. Ensure data governance compliance while collaborating with cross-functional teams to evolve data infrastructure.
Build and optimize cloud-native data pipelines on AWS using AI tooling to power analytics and ML systems. Design data models and implement governance and testing to ensure high data reliability and auditability.
Build and optimize cloud-native data pipelines and infrastructure on AWS to power AI and analytics. Design scalable data models and implement governance to ensure reliability for operational and financial reporting.
Senior Data Engineer / BI Consultant (Snowflake, dbt y Power BI) | Remoto
The White Team
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Full Time
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2 Weeks Ago
The White Team
Design, develop, and maintain data transformation processes and pipelines using dbt and Snowflake. Create and optimize Power BI dashboards and SQL queries to support data exploitation.
The role focuses on supporting the reliability, quality, and governance of the enterprise Snowflake data platform. Key duties include implementing CI/CD pipelines, monitoring data pipelines, and managing data quality and cost optimization.
Design data models and transformation logic to support self-service analytics and the Gropyus Data Fabric. Collaborate with cross-functional domain experts to deliver high-quality datasets for AI and Machine Learning use cases.
Design, build, and maintain core data platform components including ingestion frameworks and transformation pipelines. Lead strategic initiatives to scale the data ecosystem and mentor team members to improve engineering rigor.
Data Engineer, Enterprise Data, Analytics and Innovation
Vaniam Group
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Full Time
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2 Weeks Ago
Vaniam Group
Design, build, and operate reliable ETL/ELT pipelines within a Medallion architecture to ensure data reliability and scalability. Collaborate with innovation and data science teams to productionize analytics, predictive tools, and decision-support services.
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Design and build scalable Data and AI platform capabilities to support analytics, data science, and Generative AI workflows. Develop reusable frameworks and standardize data pipelines while ensuring security, reliability, and operational excellence.
Design and optimize heat rejection and HVAC systems specifically for data centers, ensuring redundancy, energy efficiency, and fault tolerance. Conduct CFD analysis and heat load calculations to optimize airflow and cooling capacity for high-profile global projects.
Develop and maintain data pipelines using Spark and Python within the Databricks platform to power the company's analytics data model. Collaborate with cross-functional teams to ensure system reliability and enable high-quality self-service analytics.
Architect and maintain a scalable data infrastructure and secure data lake to process complex geospatial datasets. Lead technical roadmaps, define engineering standards, and mentor engineers to ensure the reliability and performance of the enterprise data ecosystem.
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