דרושים Associate Devops Consultant Aws Sdt Proserve A2c

Your expertise will transform our infrastructure and deployment. You'll design scalable cloud architectures to accelerate innovation, champion a world-class DevOps culture to empower developers, and build the foundation for our future growth.

• Strategic Impact: A direct line of sight between your work and key business outcomes, with influence on strategic technical decisions across the entire business unit.

• Technical Leadership: Shape the future of our infrastructure and own the architectural roadmap for our cloud and deployment ecosystem.

• Innovation Playground: Experiment with emerging technologies and implement solutions at scale in a collaborative, forward-thinking environment.

• Technology Breadth: Work across the full DevOps spectrum – from Infrastructure as Code and Kubernetes to DataOps and developer productivity tools.
• Growth Trajectory: A clear path for career advancement as you demonstrate success and grow your leadership scope.

• Lead Technical Strategy: Define the technical vision and roadmap for our DevOps and Production Engineering capabilities, aligning multiple teams around common patterns, tools, and practices.
• Design Cloud-Native Solutions: Architect and implement secure, scalable cloud infrastructure using Kubernetes, IaC, and other modern frameworks to power our growing technology ecosystem.
• Accelerate Developer Experience: Spearhead improvements to our CI/CD pipelines, developer portals, and internal platforms to empower engineering teams to ship higher-quality software, faster.
• Optimize Data Infrastructure: Engineer and support robust platforms for our data-intensive workloads, ensuring the performance, reliability, and cost-effectiveness of systems leveraging technologies like Kafka.
• Drive DevOps Transformation: Mentor team members, lead the Production Engineering & DevOps Infra function, and collaborate with fellow R&D leaders to champion modern practices across the organization.

• Cloud Platform Expertise: Deep hands-on experience with AWS/Azure/GCP services, Kubernetes cluster management, and implementing secure, scalable cloud infrastructure architectures.
• Infrastructure as Code Mastery: Proven ability to design and implement infrastructure automation using tools like Terraform, CloudFormation, or Pulumi at enterprise scale.
• CI/CD & GitOps Expertise: Demonstrated success building and optimizing continuous integration and delivery pipelines using modern tools (e.g., GitHub Actions, Jenkins, ArgoCD).
• Data Infrastructure Knowledge: Experience designing and implementing infrastructure for data-intensive workloads, including data processing pipelines (Kafka), storage solutions, and observability systems.
• Database Expertise: Deep knowledge of relational databases (e.g., MySQL, SingleStore, PostgreSQL), including performance tuning and scalability best practices.

• Experience with big data processing applications using Spark.
• Knowledge of Machine Learning platforms such as Ray or Seldon Core.
• Proficiency in a scripting language like Python or Go for automation.
• Familiarity with DevSecOps practices and automated security tooling.
• Experience with cloud cost management and FinOps principles.

• Relocation support is not available for this position.
• Work visa/immigration sponsorship is not available for this position

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

• Technical Leadership & Architecture: Drive data infrastructure strategy and establish standardized patterns for AI/ML workloads, with direct influence on architectural decisions across data and engineering teams
• DataOps Excellence: Create seamless developer experience through self-service capabilities while significantly improving data engineer productivity and pipeline reliability metrics
• Cross-Functional Innovation: Lead collaboration between DevOps, Data Engineering, and ML Operations teams to unify our approach to infrastructure as code and orchestration platforms
• Technology Breadth & Growth: Work across the full DataOps spectrum from pipeline orchestration to AI/ML infrastructure, with clear advancement opportunities as a senior infrastructure engineer
• Strategic Business Impact: Build scalable analytics capabilities that provide direct line of sight between your infrastructure work and business outcomes through reliable, cutting-edge data solutions

• Design Data-Native Cloud Solutions - Design and implement scalable data infrastructure across multiple environments using Kubernetes, orchestration platforms, and IaC to power our AI, ML, and analytics ecosystem
• Define DataOps Technical Strategy - Shape the technical vision and roadmap for our data infrastructure capabilities, aligning DevOps, Data Engineering, and ML teams around common patterns and practices
• Accelerate Data Engineer Experience - Spearhead improvements to data pipeline deployment, monitoring tools, and self-service capabilities that empower data teams to deliver insights faster with higher reliability
• Engineer Robust Data Platforms - Build and optimize infrastructure that supports diverse data workloads from real-time streaming to batch processing, ensuring performance and cost-effectiveness for critical analytics systems
• Drive DataOps Excellence - Collaborate with engineering leaders across data teams, champion modern infrastructure practices, and mentor team members to elevate how we build, deploy, and operate data systems at scale

• 3+ years of hands-on DevOps experience building, shipping, and operating production systems.
• Coding proficiency in at least one language (e.g., Python or TypeScript); able to build production-grade automation and tools.
• Cloud platforms: deep experience with AWS, GCP, or Azure (core services, networking, IAM).
• Kubernetes: strong end-to-end understanding of Kubernetes as a system (routing/networking, scaling, security, observability, upgrades), with proven experience integrating data-centric components (e.g., Kafka, RDS, BigQuery, Aerospike).
• Infrastructure as Code: design and implement infrastructure automation using tools such as Terraform, Pulumi, or CloudFormation (modular code, reusable patterns, pipeline integration).
• GitOps & CI/CD: practical experience implementing pipelines and advanced delivery using tools such as Argo CD / Argo Rollouts, GitHub Actions, or similar.
• Observability: metrics, logs, and traces; actionable alerting and SLOs using tools such as Prometheus, Grafana, ELK/EFK, OpenTelemetry, or similar.

• Data Pipeline Orchestration - Demonstrated success building and optimizing data pipeline deployment using modern tools (Airflow, Prefect, Kubernetes operators) and implementing GitOps practices for data workloads
• Data Engineer Experience Focus - Track record of creating and improving self-service platforms, deployment tools, and monitoring solutions that measurably enhance data engineering team productivity
• Data Infrastructure Deep Knowledge - Extensive experience designing infrastructure for data-intensive workloads including streaming platforms (Kafka, Kinesis), data processing frameworks (Spark, Flink), storage solutions, and comprehensive observability systems

• Relocation support is not available for this position.
• Work visa/immigration sponsorship is not available for this position

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.