61 Hadoop jobs available for remote work from home. Apply for positions such as Engenheiro(a) de Dados e BI (Power BI), Senior Manager (Technical Lead), Lead Data Engineer | Remote, and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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You will be responsible for developing ETL pipelines using Python and PySpark, while managing large-scale data processing within Hadoop and Spark environments. Additionally, you will collaborate on projects via GitHub, monitor system performance, and implement data visualization solutions using Power BI.
The Senior Manager will oversee the development, testing, and implementation of customized software applications while managing project plans and daily operations. They are responsible for maintaining client relationships, conducting risk analysis, and coordinating with offshore development teams to ensure quality standards.
Design and implement scalable, cloud-native data platforms and pipelines while leading technical architecture and code reviews. Mentor data engineers and ensure best practices in data quality, governance, and production-grade pipeline development.
The Lead Data Engineer will architect and implement scalable data platforms and pipelines while driving the modernization of legacy assets into cloud-based Data Lakehouse environments. They will also mentor engineering teams, define technical standards, and collaborate with cross-functional stakeholders to deliver high-quality, governed data products.
Design, build, and operate large-scale data processing pipelines and analytics platforms using the Hadoop ecosystem. Ingest, transform, and analyze massive volumes of structured and unstructured data to support enterprise analytics and machine learning workloads.
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You will design and define ETL processes and data models while managing the automation and validation of data within a Big Data environment. Additionally, you will coordinate deployment processes and collaborate on various Big Data initiatives within the Market Risk department.
The Big Data Engineer will design, build, and operate large-scale data processing pipelines and analytics platforms using the Hadoop ecosystem. Responsibilities include ingesting, transforming, and analyzing massive volumes of structured and unstructured data to support enterprise analytics and machine learning workloads.
The Hadoop Big Data Developer will design, build, and operate large-scale data processing pipelines and analytics platforms. They are responsible for ingesting, transforming, and analyzing massive volumes of structured and unstructured data to support enterprise analytics and machine learning.
The Principal Software Engineer will define the end-to-end technical architecture for Generative and Agentic AI platforms while establishing engineering standards across teams. They will act as a technical authority, driving strategy, mentoring senior engineers, and resolving complex cross-functional system issues.
The Hadoop Solutions Developer will design, build, and operate large-scale data processing pipelines and analytics platforms. They are responsible for ingesting, transforming, and analyzing massive volumes of structured and unstructured data to support enterprise analytics and machine learning.
Build and improve machine learning models for personalization, search, and content recommendation across Pinterest product surfaces. Leverage advanced technologies like LLMs, deep learning, and data-driven methods to enhance content understanding and advertising algorithms.
The Forward Deployed Engineer will act as an embedded technical liaison to assist enterprise clients with platform modernization, Kubernetes architecture, and AI infrastructure deployment. They will write production code in the field, troubleshoot complex issues, and provide direct feedback to core engineering teams to improve product capabilities.
The Forward Deployed Engineer will act as an embedded technical liaison to assist enterprise clients with Kubernetes architecture, AI infrastructure setup, and stateful workload migration. They will write production code in the field and provide direct feedback to core engineering teams to improve platform capabilities.
The Data Platform Engineer will design, build, and operate large-scale data processing pipelines and analytics platforms using the Hadoop ecosystem. Responsibilities include ingesting, transforming, and analyzing massive volumes of structured and unstructured data to support enterprise analytics and machine learning workloads.
The Principal Architect will lead the technical strategy for Databricks engagements, including discovery, architecture design, and migration planning. They will also oversee project delivery, define market-facing service offerings, and collaborate with Databricks specialists to ensure successful customer outcomes.
The Senior Data Engineer will design, build, and maintain scalable data infrastructure and ingestion frameworks while collaborating with cross-functional teams. They will also provide technical guidance to junior engineers and contribute to architectural decisions to support data-driven reporting.
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The role involves administering and optimizing enterprise Big Data platforms and their underlying infrastructure using automation and AI-assisted tools. You will be responsible for managing Linux systems, databases, and containerized environments while ensuring high availability and performance.
The Data Solution Specialist will design, execute, and optimize data transformation processes while collaborating with stakeholders to integrate large healthcare datasets. They will participate in all project stages, from research and design to programming, testing, and implementation of data solutions.
Drive technical sales and adoption of Microsoft's cloud data platforms through demos, hackathons, and architecture workshops. Collaborate with enterprise customers to design secure, scalable data solutions and resolve technical blockers.
The researcher will track advanced persistent threats by leveraging global network telemetry and AI-assisted workflows to identify malicious infrastructure. They will also build automated detection pipelines and provide actionable intelligence to customers and executive leadership.
Design and build scalable, cloud-native data platforms while mentoring other engineers to foster a culture of continuous improvement. Create robust ETL/ELT pipelines and support data governance efforts to ensure data quality and lineage.
Design and build scalable, cloud-native data platforms while mentoring other engineers to foster a culture of continuous improvement. Develop robust ETL/ELT pipelines and ensure data governance, lineage, and quality across the platform.
You will build and maintain robust ETL/ELT pipelines on big data platforms while optimizing performance and cost. Additionally, you will contribute to CI/CD workflows and collaborate with product managers to develop new data-driven features.
The Data Engineer will construct, deploy, and maintain scalable data workflows across various enterprise systems including Salesforce, Oracle ERP, and SQL Server. They will also develop automated testing procedures to ensure data quality, consistency, and compliance with governance policies.
The Data Engineer will oversee ETL processes and maintain data pipelines to ensure accurate and timely data delivery for healthcare products. They will also collaborate with stakeholders to develop scalable data ingestion techniques and troubleshoot complex database issues.
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You will design, build, and optimize scalable data pipelines to integrate large volumes of data into the analytics platform. Additionally, you will collaborate with cross-functional teams to ensure data quality, governance, and system performance.
The Technical Account Manager will act as a primary technical advisor for strategic clients, managing platform architecture, operations, and best practices. They will collaborate with the Customer Success team to define engagement plans, mitigate risks, and ensure the successful implementation of Dataiku within client environments.
The Databricks Practice Lead will provide hands-on technical leadership for data engineering teams while overseeing the design and implementation of complex data platforms. This role involves managing project delivery, establishing technical standards, and serving as the primary subject-matter expert for Databricks solutions.
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