דרושים » בוגרי יחידות טכנולוגיות/אקדמיה » FinOps Engineer (Azure Focus)

As a Senior DevOps Engineer In Threat Cloud, you will be pivotal in designing, implementing, and maintaining our cloud infrastructure. You will join a highly technological team responsible for managing Threat Cloud AI cloud environments, optimizing infrastructure, and ensuring security and cost efficiency. In this role, you will collaborate with key stakeholders across the company, including R&D, Security, and Product teams, to automate processes, streamline operations, and drive impactful changes in our cloud strategy.

Key Responsibilities
Impactful Contribution: Play a major part in shaping the Threat Cloud strategy, focusing on innovation and long-term success.
Lead the team towards technical solutions guided by a strong understanding of the latest and greatest technologies like Kubernetes,, GitOps and Data Lake solutions.
Tackle large-scale production issues and bring out-of-the-box thinking to the table
Cross-Functional Collaboration: Work closely with all major stakeholders in the company, including R&D, Security, Product, and more, to ensure seamless integration of DevOps practices.
Automation & Streamlining: Help automate and streamline our operations and processes, enhancing efficiency and reducing manual intervention.
Evaluate new cloud-native technologies and vendor products to continuously improve our infrastructure

We are seeking a results-driven DevOps Team Lead to head the DevOps and Infrastructure team within our R&D organization. This role requires strategic vision, technical expertise, and a proactive approach to drive operational excellence, empower teams with robust tools and automation, and ensure high system reliability and scalability.

As the DevOps Team Lead, you will be instrumental in delivering critical KPIs, including system uptime, automation, incident management, and collaboration with development and QA teams to enable self-sufficiency. Additionally, you will serve as the leader for strategic projects, identifying opportunities to improve infrastructure and operational processes, setting long-term goals, and executing initiatives that align with Cyberints business objectives and growth.

Key Responsibilities
Strategic Leadership

Identify and lead strategic projects to enhance Cyberints platform scalability, reliability, and operational efficiency.
Develop and execute a roadmap for critical infrastructure and DevOps initiatives that drive business success.
Collaborate with senior stakeholders to align projects with organizational priorities and deliver measurable outcomes.
System Reliability & Uptime

Lead initiatives to ensure system reliability, minimize disruptions, and maintain high availability for Cyberints SaaS platform.
Establish and manage proactive monitoring, alerting, and preventive maintenance strategies.
Drive incident prevention efforts, ensuring robust failover and disaster recovery mechanisms.
Develop and maintain playbooks to enable rapid diagnosis and resolution of issues.
Automation, Infrastructure as Code (IaC), & Self-Service Enablement

Champion the adoption of automation and IaC to streamline infrastructure management and deployments.
Build and enhance self-service tools and frameworks, empowering R&D teams to operate independently with minimal reliance on DevOps.
Continuously improve CI/CD pipelines to optimize deployment speed and reliability.

Check Point is seeking a promising and talented DevOps Cloud Engineer to join our DevOps group. If you thrive in a fast-paced, dynamic environment, can handle multiple requests simultaneously, and enjoy working independently as part of a cutting-edge DevOps team, this is your opportunity to help make the world a safer place!

Key Responsibilities
Act as a DevOps Engineer within a highly skilled team, responsible for large-scale operations from development to production.
Design, develop, and maintain Avanans CI/CD solutions, including operating systems, containers, cloud orchestration, and full end-to-end automation.
Implement tools and procedures for monitoring, deployment, and alerting across our SaaS multi-tenant product family.
Participate in the large-scale migration of a highly complex system into a secured, regulation-compliant environment.
Continuously improve our cloud infrastructure to ensure fault tolerance, scalability, and security.
Plan capacity, stabilize, and enhance the performance of application infrastructure with cost efficiency and scaling in mind.
Design and shape our monitoring and logging solutions.
Execute all tasks with top-notch cloud infrastructure security as a guiding principle.

We are looking for a Site Reliability Engineer (SRE) to join our Engineering team. Someone who has a passion for observability, monitoring, automation, and high-availability systems, and who has a desire to solve complex technological challenges with a proactive approach to continuous improvement.

We use an interesting and mixed technology stack: Kubernetes, Terraform, CI/CD pipelines, Datadog, Prometheus, and cloud-native architectures.

In this position, you will use your expertise in building and scaling SRE operations, and will design, implement, and operate a world-class reliability strategy.
Key Responsibilities
Develop and maintain our monitoring, alerting, and logging systems, ensuring high visibility into production environments.
Implement automation to improve system reliability, scalability, and efficiency.
Troubleshoot and resolve production incidents, leading root cause analyses and implementing permanent fixes.
Collaborate with software engineers and DevOps teams to enhance application performance and resilience.
Continuously improve operational processes, focusing on reducing toil and improving reliability.

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
What you'll be doing
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

We are looking for a talented and experienced DevSecOps Engineer to join Check Point's IT Security group and help secure our large-scale, hybrid and multi-cloud environments.

We're a hands-on DevSecOps team embedded in the core of IT Security, focused on protecting infrastructure and network layers while building scalable, resilient systems. From AI security and data protection to CTEM (Continuous Threat Exposure Management), we lead POCs and transform innovative ideas into production-ready solutions. Were passionate about automating manual processes, driving operational excellence, and continuously evolving our security posture through cutting-edge technologies.



Key Responsibilities
Plan, Design, implement and maintain security standards and solutions across network, cloud, applications, CI/CD pipelines and secrets management all with a hands-on approach
Develop and own automation for SecOps operations, CTEM workflows and proactive security monitoring and remediation
Analyze complex system behaviors to identify performance, reliability and security issues in large-scale, live environments
Collaborate closely with SecOps and DevOps teams to align security with speed, scale and resilience
As a DevSecOps Engineer, youll play a critical role in protecting our hybrid cloud infrastructure, while shaping the future of security automation at scale.

At Similarweb, we are revolutionizing the way businesses interact with the digital world by revealing to them everything that happens online.

Our unique data and solutions empower over 4,300 customers globally, including industry giants like Google, eBay, and Adidas, to make game-changing decisions that drive their digital strategies.

In 2021, we went public on the New York Stock Exchange, and we continue to reach new heights! Come work alongside Similarwebbers across the globe who are bright, curious, practical and good people.



We are looking for a Data Engineer to join our team and help advance our Apps solution. Our product is designed to provide detailed and accurate insights into Apps Analytics, such as traffic estimation, revenue analysis, and app characterization. The role involves constructing and maintaining scalable data pipelines, developing and integrating machine learning models, and ensuring data integrity and efficiency. You will work closely with a diverse team of scientists, engineers, analysts, and collaborate with business and product stakeholders.



Key Responsibilities:

Develop and implement complex, innovative big data ML algorithms for new features, working in collaboration with data scientists and analysts.
Optimize and maintain end-to-end data pipelines using big data technologies to ensure efficiency and performance.
Monitor data pipelines to ensure data integrity and promptly troubleshoot any issues that arise.

When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.

As a Customer Engineer, you will partner with technical Sales teams as a subject matter expert in Artificial Intelligence and Machine Learning (AI/ML) to differentiate Google Cloud to our customers. You will help prospective and existing customers and partners understand the power of Google Cloud, develop creative cloud solutions and architectures to solve their business issues, engage in proofs of concepts, and troubleshoot any technical questions and roadblocks. You will use your expertise and presentation skills to engage with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. You will have excellent technical, communication and organizational skills. You will partner with internal engineering stakeholders to improve products and build solutions, optimizing for results when in production and identifying innovative ways to multiply the impact of the team as a whole.

You will be a part of a various team of Googlers working in an environment of respect where we promote equal opportunities to succeed.

Google Cloud accelerates every organizations ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Googles cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities
Work with the team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers.
Share in-depth AI/ML expertise to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, proof-of-concept work, and partnering directly with product management to prioritize solutions impacting customer adoption to Google Cloud.

At Similarweb, we are revolutionizing the way businesses interact with the digital world by revealing to them everything that happens online.

Our unique data and solutions empower over 4,300 customers globally, including industry giants like Google, eBay, and Adidas, to make game-changing decisions that drive their digital strategies.

In 2021, we went public on the New York Stock Exchange, and we continue to reach new heights! Come work alongside Similarwebbers across the globe who are bright, curious, practical and good people.



We are seeking a skilled Data/ Backend Engineer to design and implement complex, high-scale systems that retrieve, process, and analyze data from the digital world. This role involves developing and maintaining backend infrastructure, creating robust data pipelines, and ensuring the seamless operation of data-driven products and services.



Key Responsibilities:

- Design and build high-scale systems and services to support data infrastructure and production systems.

- Develop and maintain data processing pipelines using technologies such as PySpark, Hadoop, and Databricks.

- Implement dockerized high-performance microservices and manage their deployment.

- Monitor and debug backend systems and data pipelines to identify and resolve bottlenecks and failures.

- Work collaboratively with data scientists, analysts, and other engineers to develop and maintain data-driven solutions.

- Ensure data is ingested correctly from various sources and is processed efficiently.