Veja oportunidades remotas de AWS e confirme locais aceitos antes de aplicar.
Esta página reúne vagas remotas com elegibilidade de localização visível para profissionais de desenvolvimento, dados, DevOps, QA, suporte e outras áreas de TI.
Use AWS como filtro de stack sem alterar os nomes originais dos cargos, comparando senioridade, países aceitos e prontidão para aplicação.
Collaborate on impactful customer big data projects, such as creating reference architectures, developing how-to guides, and building production-ready efficient, robust and scalable tools and technologies.
Databricks · Professional Services Operations
Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration
Databricks · Professional Services Operations
Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration
Cloudflare · Accounting and Finance
Build the Future of Assurance: Develop end-to-end (full stack) applications that automate control testing, and risk monitoring across Cloudflare’s global infrastructure.
Tech Holding
Design, develop, and maintain scalable data pipelines and ETL/ELT workflows on AWS.
MediaRadar · Data Science
Build and operate pipelines: Design, build, and optimize robust ETL/ELT pipelines that move and transform millions of daily data points reliably and efficiently.
CenterWell Senior Primary Care
Bachelor's degree and 8+ years of technical experience in data engineering OR Master's degree and 4+ years of experience.
Architect, upgrade, design, and build scalable infrastructure solutions leveraging Kubernetes, AWS, RDS (MySQL/Postgres), and modern distributed patterns.
Groundtruth India Pvt Ltd · Developer
Architect Scalable Pipelines: Oversee the design and deployment of large-scale distributed data processing jobs using PySpark on Amazon EMR clusters and serverless AWS Glue ETL jobs.
Athos Commerce · Data Science
A highly collaborative team player who enjoys solving complex data problems • Passionate about building scalable and reliable systems
Moniepoint · Data Science
Build and maintain robust data pipelines processing large volumes of data
VirtusLab
Strong Python and production ML skills, with a proven track record of shipping models into real production pipelines.
CertifID · Data Science
Design, implement, and maintain ETL/ELT pipelines that pull and merge data from multiple internal and external systems, ensuring clean, reliable, and scalable data flows across the organization.
Oddball · Data Science
Build and maintain data marts, materialized views, and data pipelines within an AWS Aurora PostgreSQL environment
Honor · Data Science
Lead the architecture and development of scalable, secure, and cost-efficient data platforms on AWS.
Teamified
The Snowflake platform is scalable, performant, secure, cost-efficient, and trusted across the organisation.
Lead the design and implementation of scalable ML systems, including supervised, unsupervised, and LLM-based solutions
Dynatron Software
9:00 AM – 2:00 PM EST
B.Tech, B.E., or Master's Degree in Computer Science or a similar discipline
Particle41 · Data Science
Design, implement, and optimize Elasticsearch clusters for high-performance querying and data retrieval.
Creative Chaos · Data Science
Design and develop scalable and reliable data pipelines, ensuring high availability and performance.
Anteriad · Data Science
Partner with technical and non-technical stakeholders to translate business requirements into scalable, reliable, and maintainable data engineering solutions.
NextGen Healthcare · Data Science
Design, implement, and optimize ETL/ELT pipelines to support data ingestion and transformation from diverse healthcare data sources.
HighLevel
Architect & Scale: Design and build highly scalable and reliable backend services using Node.js, MongoDB, and ElasticSearch, ensuring optimal indexing, sharding, and query performance
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