Senior Data Engineer (Cloud)
Migrate data products and analytical workloads from legacy systems to a modern cloud data platform. Build and maintain scalable batch data pipelines while ensuring data quality and performance optimization.
33 Cloud Engineer jobs in Poland available for remote work from home. Apply for positions such as Senior Data Engineer (Cloud), Senior DevSecOps Engineer (Cloud Security / AI Platforms), C# Cloud Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Migrate data products and analytical workloads from legacy systems to a modern cloud data platform. Build and maintain scalable batch data pipelines while ensuring data quality and performance optimization.
You will develop end-to-end cloud-based software solutions for Motorola devices and fleets within an agile, cross-functional team. The role involves managing the full software development life-cycle, including requirements implementation, testing, and continuous integration.
You will architect and evolve the core M&O platform by integrating SRE principles and automating infrastructure through CI/CD pipelines. Additionally, you will implement advanced data quality monitoring and FinOps practices to ensure system reliability and cost-efficient cloud resource management.
You will design and implement a cloud-native platform architecture on GCP while building scalable guardrails for multi-team environments. Additionally, you will define cloud governance strategies and create reusable infrastructure to enable self-service provisioning.
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Design, build, and optimize scalable data processing systems and ETL/ELT pipelines within cloud and on-prem environments. Support the migration of legacy DWH systems to a Data Mesh platform while ensuring data quality and security.
Build and maintain secure, scalable cloud platforms using AWS and Azure. Support software engineering, observability, and analytics through DevSecOps automation and data platform capabilities.
Own the operational reliability and SRE lifecycle for NodeBalancer and Network Load Balancer infrastructure. This includes designing observability frameworks, leading technical incident response, and automating deployment workflows.
You will architect and optimize the CI/CD ecosystem to support massive containerized infrastructure and drive the adoption of GitOps methodologies. Your role involves collaborating with engineering teams to integrate security, quality gates, and observability into automated deployment pipelines.
The Sr. Cloud DevOps Engineer will build, automate, and operate secure, scalable multi-cloud platforms across Azure, GCP, and AWS. They will collaborate with cross-functional teams to deliver resilient infrastructure, implement automation, and support modern cloud services.
You will implement and maintain cloud security controls while conducting risk assessments and vulnerability reviews. Additionally, you will monitor cloud environments for threats and collaborate with infrastructure and development teams to ensure operational resilience.
Build and maintain production-grade ML workflows using Vertex AI and Gemini Enterprise Agent Platform Pipelines. Collaborate with engineering and data science teams to integrate ML pipelines into CI/CD processes and ensure model reliability and scalability.
You will build and maintain Python services and APIs for managing GPU virtual machines and bare-metal servers within a cloud infrastructure. Additionally, you will automate provisioning workflows, integrate hardware into Kubernetes, and investigate production issues across the control plane.
Develop and maintain RESTful APIs for managing GPU clusters and cloud infrastructure while bridging the gap between development and operations. You will participate in the full lifecycle management of compute products and design architectures focused on high availability and scalability.
The role involves designing, creating, and optimizing cloud data processing solutions and documentation in collaboration with a team. You will analyze client requirements to deliver optimal business solutions and manage potential technical risks.
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The role involves migrating data to a unified system for an insurance client and recreating business logic within the new solution. You will collaborate closely with the client to refine requirements, create documentation, and optimize system solutions.
Act as the technical escalation point for mission-critical production customers and resolve complex platform issues. Collaborate with SRE and Product teams to mitigate incidents and develop training documentation for the Core Support team.
Design and develop high-performance data pipelines and real-time processing solutions using Python and Go. Manage infrastructure as code with Terraform and ensure system reliability through monitoring and testing strategies.
Create and implement AI-based solutions and perform prompt engineering to support business potential in the public cloud. Continuously learn and integrate new AI solutions into diverse client projects.
Responsible for designing, creating, and optimizing cloud data processing solutions (ETL/ELT) and technical documentation. The role involves analyzing client business requirements to deliver optimal architectural solutions and managing potential risks.
You will be responsible for designing, developing, and optimizing cloud-based data processing solutions within a team. This includes analyzing client requirements to deliver effective business solutions and maintaining technical documentation.
You will own and evolve the platform's backend services and AWS infrastructure while contributing to real-time communication features. Responsibilities include managing CI/CD pipelines, ensuring platform reliability through monitoring, and collaborating on cross-functional product features.
Act as the final escalation point for complex Cloud infrastructure issues, diagnosing and resolving advanced incidents across compute, storage, and networking. Coordinate high-severity incident resolution with Engineering and DevOps teams while mentoring L1 and L2 engineers.
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Define and implement security practices across the AI inference stack, focusing on runtime hardening and supply chain integrity. Design security controls to protect execution environments from adversarial inputs and unauthorized access.
The Software Engineer will design, implement, and operate core platform capabilities for a global AI inference platform, focusing on secure, scalable, and reliable services across ingress, gateway, and data plane layers. Responsibilities include developing platform features like authentication, traffic handling, and OpenAI-compatible APIs, alongside contributing to observability and Kubernetes orchestration.
Develop and maintain data plane APIs and platform services for a globally distributed AI inference infrastructure. Implement authentication, authorization, and multi-tenant security controls to ensure platform isolation and compliance.
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