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Requirements:
Proven experience as a Solution Architect or in a similar role, with a strong focus on DataOps.
Deep understanding of data management principles, data modeling, and ETL processes.
Expertise in cloud technologies (AWS, Azure, GCP) and data platforms (Hadoop, Spark, Snowflake, Looker).
Strong knowledge of programming languages (Python, Java, Scala) and scripting languages (Bash, PowerShell).
Experience with DevOps tools and practices (CI/CD, containerization, orchestration).
Excellent communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.
Strong problem-solving and analytical skills
Bachelors degree in Computer Science, Engineering, or a related field.
Additional Info:
Send us your CV in English and become part of our team!
Only short-listed candidates will be contacted.
Confidentiality of all applications is assured!

Requirements:
Proven experience as a Solution Architect or in a similar role, with a
strong focus on SecOps.
Deep understanding of security principles, practices, and tools.
Expertise in cloud security technologies (AWS, Azure, GCP) and
security information and event management (SIEM) tools.
Strong knowledge of vulnerability management, penetration testing, and
incident response processes.
Experience with security automation and orchestration tools.
Excellent communication and collaboration skills, with the ability to
work effectively with both technical and non-technical stakeholders.
Strong problem-solving and analytical skills.
Bachelors degree in Computer Science, Engineering, or a related field.
Additional Info:
Send us your CV in English and become part of our team!
Only short-listed candidates will be contacted.
Confidentiality of all applications is assured!

Requirements:
1. Technical Expertise
Cloud Data Platforms: Expertise in Google Cloud Platform (GCP)
services, especially in data-related services like BigQuery, Cloud SQL,
Dataproc, Pub/Sub, and Dataflow.
Data Engineering: Strong knowledge of data pipelines, ETL/ELT
processes, and data integration using GCP tools.
Database Management: Experience with both relational and
non-relational databases, including MySQL, PostgreSQL, and NoSQL
solutions like Firestore or Bigtable.
Programming Skills: Proficiency in Python, SQL, and possibly other
languages like Java or Scala, with a focus on data manipulation and
processing.
APIs and Integrations: Experience working with Google APIs and
third-party APIs for data extraction and integration.
Machine Learning: Familiarity with Google Cloud AI tools, such as
Vertex AI, and how to integrate machine learning workflows into the data
architecture.
Data Governance: Knowledge of data security, privacy, governance, and
regulatory requirements (GDPR, HIPAA, etc.).
2. Leadership and Management
Team Management: Ability to lead a team of data engineers, analysts,
and architects, providing guidance, mentorship, and performance
management.
Project Management: Strong skills in managing data projects, ensuring
timely delivery while meeting client requirements.
Collaboration: Experience working cross-functionally with stakeholders
such as solution architects, developers, and business teams to translate
business needs into data solutions.
Resource Allocation: Efficiently managing cloud resources to optimize
cost and performance.
3. Client-Facing Skills
Consulting: Experience in providing consulting services to clients,
including understanding their data needs, providing solutions, and
guiding them through the data modernization process.
Pre-sales Support: Supporting sales teams in scoping out client
projects, preparing presentations, and explaining technical aspects of
data solutions during pre-sales.
Client Relationship Management: Building and maintaining strong
relationships with clients to ensure satisfaction and long-term
partnership.
4. Certifications and Education
Google Cloud Certifications:
Professional Data Engineer (preferred)
Professional Cloud Architect (preferred)
Other Certifications: Optional certifications in data engineering or
machine learning from organizations like Cloudera, AWS, or Microsoft
Azure can be advantageous.
Educational Background: Bachelors or Masters degree in Computer
Science, Data Science, Engineering, or a related field.
5. Soft Skills
Problem-Solving: Ability to troubleshoot data-related issues and
implement scalable solutions.
Adaptability: Ability to keep up with the rapidly changing cloud and data
landscape.
Communication: Excellent verbal and written communication skills to
explain complex data systems to non-technical stakeholders.

Requirements:
Excellent phone and cold calling skills.
Excellent verbal and written communications skills (English & Hebrew)
Ability to multitask, prioritize, and manage time efficiently.
Proficiency in CRM is an advantage.
Previous experience in an outbound sales call center or a related sales position.
Technical background.
Ability to achieve targets.
BA/BS degree or equivalent.

Requirements:
Soft Skills:
Excellent communication skills for client interactions and teamwork.
Proactive approach to problem-solving, with the ability to prioritize issues effectively and manage multiple client environments.
Advantages :
Cloud Technologies:
Familiarity with cloud technologies helps in managing scalable and cost-effective cloud resources efficiently.
Networking:
Understanding networking improves the design and management of secure cloud networks.
Additional Info:
Send us your CV in English and become part of our team!

Requirements:
Proven experience in coordinating training sessions and/or customer operations required
Strong organizational skills with attention to detail and ability to multitask.
Ability to work independently and manage multiple projects simultaneously
Excellent communication skills and a strong customer service mindset
Experience with CRM systems.
High-level proficiency in English (reading, writing, and speaking).

Requirements:
5+ years of experience working as a Full-Stack Developer with Node.js & Typescript with a strong backend orientation.
3+ years of experience with a frontend framework: React / Vue.
Hands-on experience with Elasticsearch is a strong advantage.
Experience working with cloud platforms (AWS is an advantage).
Experience using Gen AI tools a significant advantage.
Proven experience in high-scale, production-grade environments.
Familiarity with testing frameworks for both frontend and backend components.
Fast learner, self-motivated, and passionate about technology.
Team player with excellent communication skills and the ability to work independently.
Can-do attitude!

Requirements:
Requirements:
At least 3 years of experience leading engineering teams with a strong track record of mentoring, motivating, and delivering through others.
Deep hands-on expertise in one of the following technology areas:
Data Engineering: Python and Apache Airflow, with experience building data pipelines, orchestrating workflows, and creating scalable data solutions.
Full Stack Development: React and Node.js, with experience building user-facing applications and performant backend services.

Nice to Have:
Experience with generative AI platforms such as OpenAI, Anthropic, or LangChain, as well as AI engineering companions like Cursor or Claude Code.
Strong system design and architecture skills with an eye for performance, scalability, and maintainability.
Familiarity with cloud platforms and modern DevOps practices.
Understanding of data engineering fundamentals and best practices.

Requirements:
Requirements
3+ years of experience in data engineering or a related role within a production environment.
Proficiency in Python and SQL
Experience with both relational (e.g., PostgreSQL) and NoSQL databases (e.g., MongoDB, Elasticsearch).
Familiarity with big data AWS tools and frameworks such as Glue, EMR, Kinesis etc.
Experience with containerization tools like Docker and Kubernetes.
Strong understanding of data warehousing concepts and data modeling.
Excellent problem-solving skills and attention to detail.
Strong communication skills, with the ability to work collaboratively in a team environment.

Preferred Qualifications:
Experience with machine learning model deployment and MLOps practices.
Knowledge of data visualization tools and techniques.
Practical experience democratizing the companys data to enhance decision making.
Bachelors degree in Computer Science, Engineering, or a related field.

Requirements:
Required:
At least 5 years of experience in functional verification.
At least 3 years of hands-on experience with UVM / SystemVerilog.
BSc/MSc in Electrical Engineering, Computer Engineering, or Computer Science.
Proven track record in planning, executing, tracking, and closing complex verification tasks.
Strong understanding of coverage-driven verification methodologies.
Excellent problem-solving and debugging skills.
Experience working in Linux environments.
Strong communication skills and comfort working cross-functionally.
Self-motivated, detail-oriented, and capable of deep ownership.
Fluent in English, both verbal and written.

Advantages:
Experience verifying high-speed ASICs, multi-clock systems, and complex synchronization schemes.
Familiarity with high-speed interfaces such as PCIe, Aurora, Ethernet PHYs, or custom SERDES links.
Experience in full-chip or SoC-level verification.
Knowledge of scripting languages (Python, Perl, Tcl).

Requirements:
Required:
At least 5 years of experience in digital design for ASIC.
BSc/MSc in Electrical Engineering, Computer Engineering, or related field
Strong RTL development experience in Verilog/SystemVerilog.
Solid understanding of computer architecture, logic design, and digital system fundamentals.
Experience with micro-architecture specification and documentation.
Strong communication skills and the ability to work cross-functionally.
Self-driven, detail-oriented, capable of owning complex design challenges
Fluent in English, both verbal and written.

Advantages:
Experience with high-speed SERDES or parallel interfaces (PCIe, Aurora, Ethernet PHYs, custom links, etc.).
Background in high-speed ASIC design, timing closure at high frequencies, and complex synchronization schemes across clock domains.
Familiarity with verification methodologies (UVM), simulation flows, and coverage-driven verification.
Experience with scripting languages (Python, Perl, Tcl).

Requirements:
5+ years of experience in complex backend development.
Curiosity and practical experience with AI and modern development tools that foster innovation.
Proven ability to design and build scalable systems using OOP principles.
Strong experience with both relational and NoSQL databases (MongoDB; DynamoDB etc).
Hands-on experience with distributed and event-driven systems, including data-intensive environments and robust APIs.
Proven experience with AWS (Lambda, Step Functions, SQS/SNS, RDS/DynamoDB, S3, etc.).
Experience with CI/CD pipelines and adherence to code quality standards.
Fast learner with a sense of ownership, accountability, and ability to perform under pressure.
Strong ability to work across cross-functional teams, aligning technical efforts with business and operational needs.
Full professional proficiency in Hebrew and English (spoken and written).
Advantages
Background working on billing, payments, or financial systems.
Experience with automated testing.
Knowledge of Coralogix or other advanced monitoring/observability tools.