לוח משרות דרושים הייטק דאטה

Own accuracy and coverage of detection capabilities such as: technology fingerprinting, SSO/login identification, vulnerability-to-technology mapping
Build AI-powered workflows (LLM classifiers, automated rule generation) to scale detection beyond manual rule-writing
Design eval frameworks and feedback loops - golden datasets, precision/recall tracking, regression testing - to keep quality high as automation grows
Tune IP/domain discovery logic: decision rules, blacklists, thresholds, unstructured data parsing
Extend BI pipelines and schemas to enrich asset data
Investigate customer-reported detection gaps; root-cause and fix systematically

Required Senior Analyst, Market Delivery
Job Overview:
Customer Delivery Europe is in the centre of the Europe organization and the key contact between the Divisions, Operations and Technology, Global Products & Solutions and the other business units. We are close to the markets and to our customers.
Market Delivery Managers lead end-to-end project and program management for complex customer onboarding journeys, ensuring seamless integration from business impact to technical execution. They act as strategic consultants and technology relationship managers, guiding customers through operational changes, resolving technical issues, and coordinating with our subject matter experts. Their role also includes supporting TAM services, driving cross-functional collaboration, and enhancing delivery performance across local markets and key accounts.
Role:
Deliver standard projects and/or products flawlessly with high customer satisfaction
Handle medium to large customers with standard or moderately complex project scopes.
Manage basic customer escalations and non-complex operational/technical issues with support from manager or peers.
Handle PMO roles for customers and coordinate with stakeholders.

We are building a centralized intelligence system for the entire organization - a system that collects, consolidates, and analyzes all organizational data, and actively drives business workflows and decision-making.
This role exists to take that system to the next level.
As the Lead Organizational Intelligence Engineer, you will own the evolution of an internal platform that already influences how decisions are made across the company - and turn it into a foundational capability that fundamentally reshapes how the organization operates. Youll work end-to-end: from data ingestion and modeling, through analytics and AI-driven insights, all the way to decision workflows used by executives, R&D, product, and go-to-market teams.
You will operate as a senior individual contributor with broad organizational influence, while laying the technical and product foundations for a future team.
What Youll Do:
Own the architecture and implementation of a company-wide organizational intelligence system, end-to-end
Design and build data pipelines that ingest and unify data from across the organization and into our own platform
Define and evolve data models and semantic layers that create a shared, consistent language across teams and domains
Build advanced analytics and insight mechanisms that move beyond dashboards into decision-enabling workflows
Work directly with company executives to co-define requirements, identify blind spots, and translate strategic questions into systems and capabilities
Apply a product-driven mindset: deciding not just how to build, but increasingly what should be built and why
Leverage frontier AI tooling and agent-based workflows to accelerate development, improve system quality, and expand whats possible
Write and own production-grade code, setting a high bar for quality, reliability, and scalability
Influence technical and organizational workflows across the company to enable deeper intelligence and better decisions
Lay the groundwork for future externalization of these capabilities into customer-facing products

we are looking for a Senior Data Engineer.
As a Senior Data Engineer, you will be helping us design and build a flexible and scalable system that will allow our business to move fast and innovate. You will be expected to show ownership and responsibility for the code you write, but it doesn't stop there. you are encouraged to think big and help out in other areas as well.
Responsibilities:
Designing and writing code that is critical for business growth
Mastering scalability and enterprise-grade SAAS product implementation
Sense of ownership - leading design for new products and initiatives as well as integrating with currently implemented best-practices
Building and owning production-grade ETL/ELT pipelines that power analytics, ML training, and real-time AI systems
Designing data architectures that support agentic systems, including:
Embeddings and vector-based retrieval
RAG pipelines
Feedback loops and continuous improvement
Review your peer's design and code
Work closely with product managers, peer engineers, and business stakeholders

Required Data Engineer
Tel Aviv, Israel
About us:
We are international Multi-Cloud experts, utilizing the power of the cloud for smart digital transformation. With 5 sites over 4 continents around the globe, +450 experts, +1000 customers, and +30 years of proven experience, our mission is to deliver the best Multi-Cloud service to our customers, accelerate their business and help them grow. As tech-savvies, To help our customers stay on top of their game, our teams are constantly developing new strategies and tools that will help them improve cloud performance, spending, visibility, control, and automation. Our cloud experts will make any digital transformation a quick, smart, and easy process
What You'll Do:
Design, build, and maintain data pipelines and infrastructure
Develop and implement data quality checks and monitoring processes
Work with engineers to integrate data into our systems and applications
Collaborate with scientists and analysts to understand their data needs.

We are looking for a Mid-level Data Engineer to join our growing Data/MLOps team. The team is focused on building a Data/MLOps infrastructure to support the development of ML and AI algorithms for our next generation iTero scanners.
The position is suited for engineers who like to work with data, build data infrastructure and wish to support algorithm engineers.
The position is based at our Petah Tikva or Caesarea site.
Key Responsibilities
Own significant components in a data infrastructure for AI/Algorithm development.
Work with large image/3D datasets to support the development of real-life ML/AI solutions.
Work with ML / AI engineers to identify future challenges and solutions.
Own the quality of data ingestion pipelines over time.
Consistently demonstrate innovative thinking, strong partnership and high work ethics.

As a Senior Data Scientist, you will work in a highly collaborative environment with extensive amounts of data to research and develop deep learning models in the domains of dating, moderation and content segmentation and apply them to tasks such as recommendation systems and analytics at a high scale.
Responsibilities
Work with management and partner teams to design and implement solutions in recommender systems for given objectives.
Lead technical efforts to improve the performance of deep learning models and propose initiatives to impact company goals directly.
Autonomously find solutions to complex problems in social network recommendations and understand the data generation process and challenges with the data.
Analyze and leverage the extensive data received from our application to enhance model performance and accuracy.

Were looking for a Senior Data Analyst who combines strong technical skills with a strategic mindset and curiosity for how data drives user experience and growth in social mobile apps. Youll partner closely with product, engineering, and marketing teams to turn data into clear insights and measurable business impact.
If youre passionate about uncovering insights, leveraging data and AI for smarter, faster results, and driving decisions at scale; wed love to hear from you!
Responsibilities
Identify opportunities for improvement through data analysis aligned with company strategy.
Partner cross-functionally to translate data findings into actionable product and business decisions.
Design, run, and analyze A/B tests to evaluate product changes and user experience optimizations.
Build, automate, and maintain dashboards and reports to track platform health, user behavior, and key trends.
Communicate findings clearly to stakeholders, influencing both tactical and strategic decisions.
Leverage AI and automation tools to accelerate analytical workflows and uncover deeper insights.

As a Data Analyst you will be working with colleagues from various disciplines, such as - Product, Engineering, Marketing, Sales, Customer Success, Risk, Data Scientists within the team and other Data Analysts - on their KPIs, the way they observe information and the hardest questions each team is facing in order to drive insights and keep a data driven company.
You will play a key role in the ability of each team at to keep scaling!

We are looking for a motivated Data Engineer to join our growing Data team. This is an exciting opportunity to be part of a core group responsible for building, maintaining, and scaling our data platform, while working closely with Product, Engineering, and business teams.
You will play a key role in developing reliable data pipelines, ensuring data quality and consistency, and enabling data-driven decision-making across the organization.
Responsibilities:
Design, build, and maintain data pipelines and data models to support analytics and reporting needs
Work with structured data across databases, data lakes, and data warehouses
Write efficient and maintainable SQL and Python code for data transformation and validation
Ensure data quality, consistency, and basic data lineage across systems
Collaborate with Product, Engineering, and business stakeholders to understand data requirements
Support dashboards and reporting tools by providing clean, well-modeled data
Contribute to improving data standards, documentation, and best practices

What youll do:
Take full ownership, from initial design to final production, empowering you to have a tangible impact throughout the entire development process.
Thrive on solving diverse and complex problems at scale, even when faced with limited clarity on the optimal solution approach. Your ability to navigate and conquer such challenges will be highly valued.
Collaborate closely with Product Managers, Analysts, Data Scientists, and Software Engineers, working together to deliver exceptional value to our customers. Your contributions will directly contribute to shaping the success of our products.
Dive deep into analysis and optimization of performance, scalability, and stability. Your insights and improvements will have a significant impact on ensuring our technological excellence.
Embrace a continuous learning mindset, constantly exploring and evaluating new technologies. This commitment to innovation ensures that our products and systems remain at the forefront of the industry, effortlessly adapting to the ever-growing scale of our operations.
Elevate your impact by mentoring others, leading projects, and advocating for engineering best practices within your team. Your influence will extend beyond your own work, fostering a culture of growth and excellence.

We are looking for an Experienced Big Data Engineer who loves solving complex problems at an extreme scale. In this role, you arent just building "internal pipelines"-you are developing the actual product our clients interact with. You will write high-performance code, optimize your own Spark processes for client freshness, and own features end-to-end. We need a "problem solver by nature, optimizer in their soul" who brings both technical depth and a great personality to a high-speed, deep technical team.

What youll do:
Build Client-Facing Features: Design and implement high-scale product features for our premium clients - from architecture to production deployment.
Performance Engineering: Optimize scalable data pipelines and distributed processes to meet strict client SLAs. Every millisecond of freshness matters.
System Integrity: Ensure uncompromising data accuracy and performance across massive, complex datasets.
Strategic Collaboration: Partner with upstream data providers, client-side teams, and Product Managers to turn raw events into production-grade features.

We are looking for an AI Enablement Tech Lead to lead the development of AI-native data capabilities and drive the adoption of AI across analytics workflows.
This role is part of the Analytics & AI Enablement group within the data department and is responsible for establishing the foundational data and AI capabilities that support advanced use cases, including chat with data, autonomous analytics, and AI-driven decision-making.
You will act as a technical and strategic bridge between data, engineering, and AI platform teams - owning the design of AI-ready data layers, and taking a significant part in the specification and orchestration of data-ready agent solutions and analytical workflows, from ideation to production.
You are a hands-on builder and a transformation leader, with proven experience delivering AI solutions and a strong foundation in data and analytics.
Hybrid
Full-time
What youll do: 
Define and build AI-ready data foundations, including semantic layers optimized for LLM and AI consumption
Design and standardize AI-native analytics workflows, combining data modeling, LLMs, and orchestration frameworks
Partner with Data Engineering and AI platform teams to shape infrastructure, tooling, and data interfaces for AI use
Drive experimentation with new AI capabilities and rapidly iterate from POC to scalable solutions
Establish best practices for AI usage in analytics, including prompt design, evaluation, monitoring, and governance
Act as a technical leader and mentor, driving AI knowledge and adoption across the analytics community.

We're looking for a Data Engineer with 4+ year experience to join our Data Engineering team and help us build and scale our production-grade data platform. You'll work on high-performance systems built on self-hosted ClickHouse, optimize complex data pipelines, and collaborate closely with Product, Analytics, and Infrastructure teams to deliver reliable, fast, and scalable data solutions.

This is a hands-on technical role where you'll have a significant impact on how we ingest, model, store, and serve data that powers our analytics and AI-driven products.
Youll play a key role in shaping the direction of our data platform and have meaningful ownership over critical components of our architecture.

What You'll Do:
Data Modeling & Architecture
Design and evolve data models that reflect business logic and support analytical use cases
Collaborate with the BI and Analytics teams to understand data requirements and translate them into efficient schemas
Performance Optimization
Optimize ClickHouse schemas, partitioning strategies, indexing, and compression
Profile and tune slow queries to improve performance and reduce costs
Implement systems that ensure data quality, consistency, and operational efficiency (e.g., deduplication, validation, anomaly detection)
Monitor pipeline health, data freshness, and query performance with appropriate alerting mechanisms
SQL Compiler Development
Develop and maintain the SQL Compiler layer that translates high-level queries into optimized ClickHouse execution plansImplement query optimization and rewriting strategies to improve performanceDebug and resolve compiler issues to ensure accurate and efficient query translation

Data Pipeline Development & Collaboration
Review and advise the Integration team on pipeline architecture, performance, and best practices.
Provide guidance on data modeling, schema design, and optimization for new data sources.
Troubleshoot and maintain existing pipelines when issues arise or optimization is needed
Ensure data freshness, reliability, and quality across all ingestion pipelines.
Collaboration & Support
Work closely with the Integration team to ensure smooth data ingestion from new sources.
Partner with Infrastructure to support high availability and disaster recovery
Support other teams across the company in accessing and using data effectively.

We are looking for a Senior Data & Machine Learning Engineer to operate at the intersection of data platform engineering and machine learning enablement. This role is responsible for building scalable, efficient, and reliable data systems while enabling Data Science and Analytics teams to develop and deploy ML-driven features.

You will take ownership of the data and ML infrastructure layer, ensuring that pipelines, storage models, and compute usage are optimized, while also shaping how data workflows and ML solutions are designed across the organization.


Responsibilities
Data Platform & Infrastructure

Design, build, and maintain scalable data pipelines and storage systems supporting analytics and ML use cases
Ensure compute and cost efficiency across pipelines, storage models, and processing workflows
Own and improve data orchestration, transformation, and serving layers (e.g., Spark, DBT, streaming/batch systems)
Build and maintain shared infrastructure components, including:
IO managers and data access abstractions
Integrations with DBT, Spark, and other data frameworks
Internal tooling to improve developer productivity and reliability
ML Enablement & Collaboration

Partner closely with Data Science to design and productions ML solutions for new features and research initiatives
Translate experimental models into robust, scalable production systems
Support feature engineering, training pipelines, and inference workflows
Help define best practices for ML lifecycle management (training, validation, deployment, monitoring)
Data Quality, Governance & Best Practices

Enforce best practices for building and maintaining data processes across Data Analyst and Data Science teams
Define standards for:
Data modeling and transformations
Pipeline reliability and observability
Testing, versioning, and documentation
Improve data quality, consistency, and discoverability across the organization
Performance & Reliability

Optimize systems for performance, scalability, and cost efficiency
Monitor and troubleshoot data pipelines and ML systems in production
Implement observability (logging, metrics, alerting) across data workflows